[{"data":1,"prerenderedAt":1609},["ShallowReactive",2],{"9JJStFeYqd":3,"P72sMQvZBU":668,"LvkDVc1x6Q":1401,"YnurNikDvR":1606},{"siteConfiguration":4,"navigations":130},{"id":5,"siteName":6,"siteDescription":7,"ieee":8,"createdAt":9,"updatedAt":10,"url_path_id":11,"dateFormat":12,"favicon":13,"header":56,"socialLinks":105,"footer":113,"seoMeta":119,"url_path":114},1,"CDC 2024","2024 Conference on Decision and Control",true,"2023-02-24T04:12:04.085Z","2024-12-15T00:11:06.545Z","2","DDDD",{"id":14,"name":15,"alternativeText":16,"caption":16,"width":17,"height":18,"formats":19,"hash":50,"ext":21,"mime":24,"size":51,"url":52,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":54,"updatedAt":55},4,"CDC logo",null,1945,2095,{"large":20,"small":29,"medium":36,"thumbnail":43},{"ext":21,"url":22,"hash":23,"mime":24,"name":25,"path":16,"size":26,"width":27,"height":28},".png","https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_IEEE_CSS_Logo_Mark_e9973ad670.png","large_IEEE_CSS_Logo_Mark_e9973ad670","image/png","large_CDC logo",159.05,928,1000,{"ext":21,"url":30,"hash":31,"mime":24,"name":32,"path":16,"size":33,"width":34,"height":35},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_IEEE_CSS_Logo_Mark_e9973ad670.png","small_IEEE_CSS_Logo_Mark_e9973ad670","small_CDC logo",53.38,464,500,{"ext":21,"url":37,"hash":38,"mime":24,"name":39,"path":16,"size":40,"width":41,"height":42},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_IEEE_CSS_Logo_Mark_e9973ad670.png","medium_IEEE_CSS_Logo_Mark_e9973ad670","medium_CDC logo",91.86,696,750,{"ext":21,"url":44,"hash":45,"mime":24,"name":46,"path":16,"size":47,"width":48,"height":49},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_IEEE_CSS_Logo_Mark_e9973ad670.png","thumbnail_IEEE_CSS_Logo_Mark_e9973ad670","thumbnail_CDC logo",11.75,145,156,"IEEE_CSS_Logo_Mark_e9973ad670",73.2,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/IEEE_CSS_Logo_Mark_e9973ad670.png","strapi-provider-upload-aws-s3-advanced","2023-02-25T01:06:57.287Z","2024-04-29T03:44:21.923Z",{"id":5,"headerBackground":57,"siteLogo":58,"buttons":93,"affiliate":16},"base-100",{"id":59,"name":60,"alternativeText":16,"caption":16,"width":61,"height":62,"formats":63,"hash":89,"ext":21,"mime":24,"size":90,"url":91,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":92,"updatedAt":92},70,"Logo CDC 2024 3.png",4085,1178,{"large":64,"small":70,"medium":76,"thumbnail":82},{"ext":21,"url":65,"hash":66,"mime":24,"name":67,"path":16,"size":68,"width":28,"height":69},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_Logo_CDC_2024_3_7579d1caa7.png","large_Logo_CDC_2024_3_7579d1caa7","large_Logo CDC 2024 3.png",58.06,288,{"ext":21,"url":71,"hash":72,"mime":24,"name":73,"path":16,"size":74,"width":35,"height":75},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_Logo_CDC_2024_3_7579d1caa7.png","small_Logo_CDC_2024_3_7579d1caa7","small_Logo CDC 2024 3.png",21.7,144,{"ext":21,"url":77,"hash":78,"mime":24,"name":79,"path":16,"size":80,"width":42,"height":81},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_Logo_CDC_2024_3_7579d1caa7.png","medium_Logo_CDC_2024_3_7579d1caa7","medium_Logo CDC 2024 3.png",38.48,216,{"ext":21,"url":83,"hash":84,"mime":24,"name":85,"path":16,"size":86,"width":87,"height":88},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_Logo_CDC_2024_3_7579d1caa7.png","thumbnail_Logo_CDC_2024_3_7579d1caa7","thumbnail_Logo CDC 2024 3.png",9.4,245,71,"Logo_CDC_2024_3_7579d1caa7",83.25,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/Logo_CDC_2024_3_7579d1caa7.png","2024-04-29T03:49:05.513Z",{"id":94,"variation":95,"button":96},21,"Buttons Left",[97],{"id":98,"label":99,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":104,"newWindow":8,"downloadable":16,"shape":16},22,"Conference Program Book (PDF)","btn-sm","btn-primary","ChevronRightIcon","End","https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/CDC_2024_Conference_Program_c0c97763c6.pdf",[106,109],{"id":5,"url":107,"platform":108},"https://twitter.com/IEEECDC2024","Twitter",{"id":110,"url":111,"platform":112},2,"https://www.linkedin.com/in/ieee-cdc-social/","Linkedin",{"id":5,"prose":114,"confcatsFooter":8,"affiliatesFooter":16,"styles":115},"",{"id":116,"edgeTop":117,"edgeBottom":117,"background":118,"containerWidth":16},10,"None","primary",{"id":5,"eventAttendanceMode":120,"startDate":121,"endDate":122,"eventStatus":123,"previousStartDate":16,"locationName":124,"locationStreetAddress":125,"addressLocality":126,"addressRegion":16,"addressCountry":127,"registrationUrl":16,"postalCode":128,"locationUrl":129,"isEvent":8,"affiliate":16},"OfflineEventAttendanceMode","2024-12-16T06:00:00.000Z","2024-12-19T06:00:00.000Z","EventScheduled","Milano Congressi (MiCo) Conference Center","P.le Carlo Magno, 1","Milano","Italy","20149","https://aipc.org/member/mico-milano-convention-centre/",{"mainNavigation":131,"footerNavigation":662},[132,214,319,336,395,485,601,644],{"id":110,"title":133,"menuAttached":8,"order":5,"path":134,"type":135,"uiRouterKey":136,"slug":137,"external":138,"items":139},"About","/about","WRAPPER","about","about-2",false,[140,161,179,196],{"id":14,"title":141,"menuAttached":8,"order":5,"path":142,"type":143,"uiRouterKey":144,"slug":145,"external":138,"related":146,"items":160},"CDC History","/about/cdc-history","INTERNAL","cdc-history","about-cdc-history",{"id":110,"heading":141,"createdAt":147,"updatedAt":148,"publishedAt":149,"url_path_id":150,"__contentType":151,"pathAlias":152,"navigationItemId":14,"createdBy":157,"updatedBy":158,"__templateName":159},"2023-02-24T17:13:51.847Z","2023-07-08T12:13:27.286Z","2023-02-24T17:14:46.651Z","6","api::page.page",{"id":153,"url_path":154,"generated":8,"contenttype":151,"createdAt":155,"updatedAt":156},6,"/cdc-history","2023-02-24T17:13:51.861Z","2023-07-08T12:13:27.307Z",{},{},"Generic",[],{"id":162,"title":163,"menuAttached":8,"order":110,"path":164,"type":143,"uiRouterKey":165,"slug":166,"external":138,"related":167,"items":178},5,"Committees","/about/committees","committees","about-committees",{"id":168,"heading":163,"createdAt":169,"updatedAt":170,"publishedAt":171,"url_path_id":172,"__contentType":151,"pathAlias":173,"navigationItemId":162,"createdBy":176,"updatedBy":177,"__templateName":159},3,"2023-02-24T21:00:42.678Z","2024-11-18T12:12:52.878Z","2023-02-24T21:00:44.021Z","7",{"id":174,"url_path":164,"generated":138,"contenttype":151,"createdAt":175,"updatedAt":175},7,"2023-02-24T21:00:42.690Z",{},{},[],{"id":168,"title":180,"menuAttached":8,"order":168,"path":181,"type":143,"uiRouterKey":182,"slug":183,"external":138,"related":184,"items":195},"Call For Papers","/about/call-for-papers","call-for-papers","about-call-for-papers",{"id":14,"heading":185,"createdAt":186,"updatedAt":187,"publishedAt":188,"url_path_id":189,"__contentType":151,"pathAlias":190,"navigationItemId":168,"createdBy":193,"updatedBy":194,"__templateName":159},"Call for Papers","2023-02-24T21:01:15.453Z","2024-02-28T20:18:10.720Z","2023-02-24T21:01:16.857Z","8",{"id":191,"url_path":181,"generated":138,"contenttype":151,"createdAt":192,"updatedAt":192},8,"2023-02-24T21:01:15.460Z",{},{},[],{"id":197,"title":198,"menuAttached":8,"order":14,"path":199,"type":143,"uiRouterKey":200,"slug":201,"external":138,"related":202,"items":213},33,"Author Information","/about/author-information","author-information","about-author-information",{"id":162,"heading":198,"createdAt":203,"updatedAt":204,"publishedAt":205,"url_path_id":206,"__contentType":151,"pathAlias":207,"navigationItemId":197,"createdBy":211,"updatedBy":212,"__templateName":159},"2023-02-24T21:01:37.176Z","2024-07-23T09:44:14.644Z","2023-02-24T21:01:38.155Z","9",{"id":208,"url_path":199,"generated":138,"contenttype":151,"createdAt":209,"updatedAt":210},9,"2023-02-24T21:01:37.183Z","2024-07-23T09:44:14.676Z",{},{},[],{"id":153,"title":215,"menuAttached":8,"order":110,"path":216,"type":135,"uiRouterKey":217,"slug":218,"external":138,"items":219},"Program","/program","program","program-1",[220,227,244,262,281,299],{"id":221,"title":222,"menuAttached":8,"order":5,"path":223,"type":224,"uiRouterKey":225,"slug":226,"external":8},35,"Conference Program","https://css.paperplaza.net/conferences/conferences/CDC24/program/","EXTERNAL","conference-program-1",{},{"id":208,"title":228,"menuAttached":8,"order":110,"path":229,"type":143,"uiRouterKey":230,"slug":231,"external":138,"related":232,"items":243},"Plenary Speakers","/program/plenzry-speakers","plenary-speakers-1","program-plenzry-speakers",{"id":153,"heading":228,"createdAt":233,"updatedAt":234,"publishedAt":235,"url_path_id":236,"__contentType":151,"pathAlias":237,"navigationItemId":208,"createdBy":241,"updatedBy":242,"__templateName":159},"2023-02-24T21:01:56.625Z","2024-12-13T14:00:19.704Z","2023-02-24T21:01:58.918Z","10",{"id":116,"url_path":238,"generated":138,"contenttype":151,"createdAt":239,"updatedAt":240},"/program/plenary-speakers","2023-02-24T21:01:56.631Z","2024-03-01T16:08:07.110Z",{},{},[],{"id":116,"title":245,"menuAttached":8,"order":168,"path":246,"type":143,"uiRouterKey":247,"slug":248,"external":138,"related":249,"items":261},"Workshops","/program/workshops-live","workshops-1","program-workshops-live",{"id":250,"heading":251,"createdAt":252,"updatedAt":253,"publishedAt":254,"url_path_id":255,"__contentType":151,"pathAlias":256,"navigationItemId":116,"createdBy":259,"updatedBy":260,"__templateName":159},31,"Workshops ","2024-07-17T20:03:00.173Z","2024-11-18T12:28:40.928Z","2024-07-20T04:24:24.412Z","70",{"id":59,"url_path":246,"generated":138,"contenttype":151,"createdAt":257,"updatedAt":258},"2024-07-17T20:03:00.190Z","2024-07-19T17:54:19.093Z",{},{},[],{"id":263,"title":264,"menuAttached":8,"order":14,"path":265,"type":143,"uiRouterKey":266,"slug":267,"external":138,"related":268,"items":280},30,"Tutorials","/program/Tutorials","tutorials","program-tutorials",{"id":263,"heading":264,"createdAt":269,"updatedAt":270,"publishedAt":271,"url_path_id":272,"__contentType":151,"pathAlias":273,"navigationItemId":263,"createdBy":278,"updatedBy":279,"__templateName":159},"2024-07-16T23:07:52.158Z","2024-10-22T09:17:54.138Z","2024-07-17T00:40:11.762Z","61",{"id":274,"url_path":275,"generated":138,"contenttype":151,"createdAt":276,"updatedAt":277},61,"/program/tutorials","2024-07-16T23:07:52.169Z","2024-07-16T23:07:57.720Z",{},{},[],{"id":282,"title":283,"menuAttached":8,"order":162,"path":284,"type":143,"uiRouterKey":285,"slug":286,"external":138,"related":287,"items":298},42,"Competitions","/program/competitions","competitions","program-competitions",{"id":288,"heading":283,"createdAt":289,"updatedAt":290,"publishedAt":291,"url_path_id":292,"__contentType":151,"pathAlias":293,"navigationItemId":282,"createdBy":296,"updatedBy":297,"__templateName":159},45,"2024-09-27T10:16:16.085Z","2024-09-28T01:20:41.188Z","2024-09-27T10:19:25.973Z","151",{"id":294,"url_path":284,"generated":138,"contenttype":151,"createdAt":295,"updatedAt":295},151,"2024-09-27T10:16:16.090Z",{},{},[],{"id":300,"title":301,"menuAttached":8,"order":153,"path":302,"type":143,"uiRouterKey":303,"slug":304,"external":138,"related":305,"items":318},44,"Session Guidelines","/program/session-guidelines","session-guidelines","program-session-guidelines",{"id":306,"heading":301,"createdAt":307,"updatedAt":308,"publishedAt":309,"url_path_id":310,"__contentType":151,"pathAlias":311,"navigationItemId":300,"createdBy":316,"updatedBy":317,"__templateName":159},46,"2024-12-04T07:33:59.960Z","2024-12-07T16:54:26.390Z","2024-12-04T07:37:25.466Z","162",{"id":312,"url_path":313,"generated":138,"contenttype":151,"createdAt":314,"updatedAt":315},162,"/session-guidelines","2024-12-04T07:33:59.976Z","2024-12-05T06:44:55.718Z",{},{},[],{"id":320,"title":321,"menuAttached":8,"order":168,"path":322,"type":143,"uiRouterKey":323,"slug":323,"external":138,"related":324,"items":335},36,"Registration","/registration","registration-1",{"id":174,"heading":321,"createdAt":325,"updatedAt":326,"publishedAt":327,"url_path_id":328,"__contentType":151,"pathAlias":329,"navigationItemId":320,"createdBy":333,"updatedBy":334,"__templateName":159},"2023-02-24T21:02:25.548Z","2024-12-04T11:56:22.103Z","2024-07-26T03:23:33.946Z","11",{"id":330,"url_path":322,"generated":8,"contenttype":151,"createdAt":331,"updatedAt":332},11,"2023-02-24T21:02:25.558Z","2024-12-04T11:56:22.127Z",{},{},[],{"id":330,"title":337,"menuAttached":8,"order":14,"path":338,"type":135,"uiRouterKey":339,"slug":340,"external":138,"items":341},"Students","/students","students","students-1",[342,360,377],{"id":343,"title":344,"menuAttached":8,"order":5,"path":345,"type":143,"uiRouterKey":346,"slug":347,"external":138,"related":348,"items":359},12,"Student Travel & Workshop Support","/students/student-travel-support","student-travel-and-workshop-support","students-student-travel-support",{"id":208,"heading":344,"createdAt":349,"updatedAt":350,"publishedAt":351,"url_path_id":352,"__contentType":151,"pathAlias":353,"navigationItemId":343,"createdBy":357,"updatedBy":358,"__templateName":159},"2023-02-24T21:03:52.223Z","2024-08-15T01:43:45.634Z","2023-02-24T21:03:55.279Z","13",{"id":354,"url_path":345,"generated":138,"contenttype":151,"createdAt":355,"updatedAt":356},13,"2023-02-24T21:03:52.233Z","2023-07-13T20:37:34.169Z",{},{},[],{"id":354,"title":361,"menuAttached":8,"order":110,"path":362,"type":143,"uiRouterKey":363,"slug":364,"external":138,"related":365,"items":376},"Best Student Paper Award","/students/best-student-paper-award","best-student-paper-award-1","students-best-student-paper-award",{"id":366,"heading":361,"createdAt":367,"updatedAt":368,"publishedAt":369,"url_path_id":370,"__contentType":151,"pathAlias":371,"navigationItemId":354,"createdBy":374,"updatedBy":375,"__templateName":159},37,"2024-07-26T11:49:50.162Z","2024-07-26T11:56:05.334Z","2024-07-26T11:51:43.979Z","117",{"id":372,"url_path":362,"generated":138,"contenttype":151,"createdAt":373,"updatedAt":373},117,"2024-07-26T11:49:50.166Z",{},{},[],{"id":98,"title":378,"menuAttached":8,"order":168,"path":379,"type":143,"uiRouterKey":380,"slug":381,"external":138,"related":382,"items":394},"Meet the Faculty Candidates Poster Session","/students/meet-the-faculty-candidates-poster-session","meet-the-faculty-candidates-poster-session","students-meet-the-faculty-candidates-poster-session",{"id":383,"heading":384,"createdAt":385,"updatedAt":386,"publishedAt":387,"url_path_id":388,"__contentType":151,"pathAlias":389,"navigationItemId":98,"createdBy":392,"updatedBy":393,"__templateName":159},20,"Meet the Faculty Candidates Poster Session ","2023-07-13T15:25:19.260Z","2024-11-18T13:17:53.916Z","2023-07-13T15:25:31.594Z","42",{"id":282,"url_path":379,"generated":138,"contenttype":151,"createdAt":390,"updatedAt":391},"2023-07-13T15:25:19.280Z","2023-07-13T15:25:29.975Z",{},{},[],{"id":396,"title":397,"menuAttached":8,"order":162,"path":398,"type":135,"uiRouterKey":399,"slug":399,"external":138,"related":400,"items":411},14,"Events","/events","events-1",{"id":330,"heading":397,"createdAt":401,"updatedAt":402,"publishedAt":403,"url_path_id":404,"__contentType":151,"pathAlias":405,"navigationItemId":396,"createdBy":409,"updatedBy":410,"__templateName":159},"2023-02-24T21:05:16.430Z","2023-02-24T21:05:18.392Z","2023-02-24T21:05:18.378Z","15",{"id":406,"url_path":398,"generated":8,"contenttype":151,"createdAt":407,"updatedAt":408},15,"2023-02-24T21:05:16.438Z","2023-02-24T21:05:18.407Z",{},{},[412,430,449,466],{"id":413,"title":414,"menuAttached":8,"order":5,"path":415,"type":143,"uiRouterKey":416,"slug":417,"external":138,"related":418,"items":429},38,"Social Program","/events/social-program","social-program","events-social-program",{"id":282,"heading":414,"createdAt":419,"updatedAt":420,"publishedAt":421,"url_path_id":422,"__contentType":151,"pathAlias":423,"navigationItemId":413,"createdBy":427,"updatedBy":428,"__templateName":159},"2024-08-22T07:37:14.397Z","2024-11-14T10:20:49.292Z","2024-08-22T07:45:26.511Z","136",{"id":424,"url_path":415,"generated":138,"contenttype":151,"createdAt":425,"updatedAt":426},136,"2024-08-22T07:37:14.402Z","2024-08-23T07:11:37.410Z",{},{},[],{"id":431,"title":432,"menuAttached":8,"order":110,"path":433,"type":143,"uiRouterKey":434,"slug":435,"external":138,"related":436,"items":448},40,"Special Sessions","/events/special-sessions","special-sessions-1","events-special-sessions",{"id":437,"heading":432,"createdAt":438,"updatedAt":439,"publishedAt":440,"url_path_id":441,"__contentType":151,"pathAlias":442,"navigationItemId":431,"createdBy":446,"updatedBy":447,"__templateName":159},41,"2024-08-09T06:13:30.799Z","2024-11-07T22:11:37.374Z","2024-08-09T06:17:29.330Z","133",{"id":443,"url_path":433,"generated":138,"contenttype":151,"createdAt":444,"updatedAt":445},133,"2024-08-09T06:13:30.806Z","2024-08-22T07:51:45.102Z",{},{},[],{"id":437,"title":450,"menuAttached":8,"order":168,"path":451,"type":143,"uiRouterKey":452,"slug":453,"external":138,"related":454,"items":465},"Demos","/events/Demos","demos","events-demos",{"id":300,"heading":450,"createdAt":455,"updatedAt":456,"publishedAt":457,"url_path_id":458,"__contentType":151,"pathAlias":459,"navigationItemId":437,"createdBy":463,"updatedBy":464,"__templateName":159},"2024-09-15T00:54:33.133Z","2024-11-08T23:16:48.335Z","2024-09-15T05:36:05.489Z","146",{"id":460,"url_path":461,"generated":138,"contenttype":151,"createdAt":462,"updatedAt":462},146,"/events/demos","2024-09-15T00:54:33.140Z",{},{},[],{"id":467,"title":468,"menuAttached":8,"order":14,"path":469,"type":143,"uiRouterKey":470,"slug":471,"external":138,"related":472,"items":484},43,"Meeting Schedule","/events/meeting-schedule","meeting-schedule-1","events-meeting-schedule",{"id":473,"heading":468,"createdAt":474,"updatedAt":475,"publishedAt":476,"url_path_id":477,"__contentType":151,"pathAlias":478,"navigationItemId":467,"createdBy":482,"updatedBy":483,"__templateName":159},47,"2024-12-04T09:39:59.111Z","2024-12-04T14:02:59.194Z","2024-12-04T09:53:23.110Z","163",{"id":479,"url_path":469,"generated":138,"contenttype":151,"createdAt":480,"updatedAt":481},163,"2024-12-04T09:39:59.127Z","2024-12-04T14:02:59.208Z",{},{},[],{"id":406,"title":486,"menuAttached":8,"order":153,"path":487,"type":135,"uiRouterKey":488,"slug":489,"external":138,"items":490},"Travel & Venue","/travel-and-venue","travel-1","travel-and-venue",[491,510,530,548,565,582],{"id":492,"title":493,"menuAttached":8,"order":5,"path":494,"type":143,"uiRouterKey":495,"slug":496,"external":138,"related":497,"items":509},27,"About Milan","/travel-and-venue/about-milan","about-milan","travel-and-venue-about-milan",{"id":498,"heading":493,"createdAt":499,"updatedAt":500,"publishedAt":501,"url_path_id":502,"__contentType":151,"pathAlias":503,"navigationItemId":492,"createdBy":507,"updatedBy":508,"__templateName":159},24,"2024-02-26T23:05:49.562Z","2024-02-27T15:29:41.101Z","2024-02-27T15:29:41.084Z","51",{"id":504,"url_path":494,"generated":138,"contenttype":151,"createdAt":505,"updatedAt":506},51,"2024-02-26T23:05:49.573Z","2024-02-26T23:05:59.845Z",{},{},[],{"id":511,"title":512,"menuAttached":8,"order":110,"path":513,"type":143,"uiRouterKey":514,"slug":515,"external":138,"related":516,"items":529},28,"How to Reach MIlan","/travel-and-venue/how-to-reach-milan","how-to-reach-m-ilan","travel-and-venue-how-to-reach-milan",{"id":517,"heading":518,"createdAt":519,"updatedAt":520,"publishedAt":521,"url_path_id":522,"__contentType":151,"pathAlias":523,"navigationItemId":511,"createdBy":527,"updatedBy":528,"__templateName":159},25,"How to Reach Milan","2024-02-26T23:40:30.411Z","2024-02-27T15:29:27.129Z","2024-02-27T15:29:27.113Z","52",{"id":524,"url_path":513,"generated":138,"contenttype":151,"createdAt":525,"updatedAt":526},52,"2024-02-26T23:40:30.421Z","2024-02-26T23:40:37.959Z",{},{},[],{"id":517,"title":531,"menuAttached":8,"order":168,"path":532,"type":143,"uiRouterKey":533,"slug":534,"external":138,"related":535,"items":547},"Accommodation","/travel-and-venue/accomodations","accommodation","travel-and-venue-accomodations",{"id":536,"heading":531,"createdAt":537,"updatedAt":538,"publishedAt":539,"url_path_id":540,"__contentType":151,"pathAlias":541,"navigationItemId":517,"createdBy":545,"updatedBy":546,"__templateName":159},26,"2024-02-26T23:46:28.109Z","2024-12-09T17:49:48.948Z","2024-02-27T15:29:36.317Z","53",{"id":542,"url_path":532,"generated":138,"contenttype":151,"createdAt":543,"updatedAt":544},53,"2024-02-26T23:46:28.117Z","2024-02-26T23:46:50.467Z",{},{},[],{"id":498,"title":549,"menuAttached":8,"order":14,"path":550,"type":143,"uiRouterKey":551,"slug":552,"external":138,"related":553,"items":564},"The Conference Venue","/travel-and-venue/the-conference-venue","the-conference-venue","travel-and-venue-the-conference-venue",{"id":492,"heading":549,"createdAt":554,"updatedAt":555,"publishedAt":556,"url_path_id":557,"__contentType":151,"pathAlias":558,"navigationItemId":498,"createdBy":562,"updatedBy":563,"__templateName":159},"2024-02-26T23:53:15.588Z","2024-11-18T12:33:32.252Z","2024-02-27T15:29:19.840Z","54",{"id":559,"url_path":550,"generated":138,"contenttype":151,"createdAt":560,"updatedAt":561},54,"2024-02-26T23:53:15.597Z","2024-02-26T23:53:23.110Z",{},{},[],{"id":536,"title":566,"menuAttached":8,"order":162,"path":567,"type":143,"uiRouterKey":568,"slug":569,"external":138,"related":570,"items":581},"Sustainability","/travel-and-venue/sustainability","sustainability","travel-and-venue-sustainability",{"id":511,"heading":566,"createdAt":571,"updatedAt":572,"publishedAt":573,"url_path_id":574,"__contentType":151,"pathAlias":575,"navigationItemId":536,"createdBy":579,"updatedBy":580,"__templateName":159},"2024-02-27T00:09:00.120Z","2024-12-07T09:09:42.716Z","2024-02-27T15:29:15.589Z","55",{"id":576,"url_path":567,"generated":138,"contenttype":151,"createdAt":577,"updatedAt":578},55,"2024-02-27T00:09:00.131Z","2024-02-27T00:09:08.349Z",{},{},[],{"id":583,"title":584,"menuAttached":8,"order":153,"path":585,"type":143,"uiRouterKey":586,"slug":587,"external":138,"related":588,"items":600},29,"Visa and Letter","/travel-and-venue/visas-and-certificates","visa-and-letter","travel-and-venue-visas-and-certificates",{"id":583,"heading":584,"createdAt":589,"updatedAt":590,"publishedAt":591,"url_path_id":592,"__contentType":151,"pathAlias":593,"navigationItemId":583,"createdBy":598,"updatedBy":599,"__templateName":159},"2024-07-12T21:04:53.152Z","2024-10-07T13:11:52.133Z","2024-07-12T22:06:47.947Z","60",{"id":594,"url_path":595,"generated":138,"contenttype":151,"createdAt":596,"updatedAt":597},60,"/travel-and-venue/visa-and-certificates","2024-07-12T21:04:53.185Z","2024-07-12T21:27:02.453Z",{},{},[],{"id":602,"title":603,"menuAttached":8,"order":174,"path":604,"type":135,"uiRouterKey":605,"slug":606,"external":138,"items":607},19,"Exhibits & Sponsors","/exhibitor-sponsor","exhibits-and-sponsors","exhibitor-sponsor",[608,625],{"id":366,"title":609,"menuAttached":8,"order":5,"path":610,"type":143,"uiRouterKey":611,"slug":612,"external":138,"related":613,"items":624},"Sponsors","/exhibitor-sponsor/sponsors","sponsors-1","exhibitor-sponsor-sponsors",{"id":221,"heading":609,"createdAt":614,"updatedAt":615,"publishedAt":616,"url_path_id":617,"__contentType":151,"pathAlias":618,"navigationItemId":366,"createdBy":622,"updatedBy":623,"__templateName":159},"2024-07-26T00:01:30.421Z","2024-11-18T12:52:04.437Z","2024-07-26T01:36:17.467Z","113",{"id":619,"url_path":620,"generated":138,"contenttype":151,"createdAt":621,"updatedAt":621},113,"/exhibitors-and-sponsors/sponsors","2024-07-26T00:01:30.427Z",{},{},[],{"id":626,"title":627,"menuAttached":8,"order":110,"path":628,"type":143,"uiRouterKey":629,"slug":630,"external":138,"related":631,"items":643},23,"Call for Exhibitors & Sponsors","/exhibitor-sponsor/become-a-sponsor","call-for-exhibitors","exhibitor-sponsor-become-a-sponsor",{"id":98,"heading":632,"createdAt":633,"updatedAt":634,"publishedAt":635,"url_path_id":636,"__contentType":151,"pathAlias":637,"navigationItemId":626,"createdBy":641,"updatedBy":642,"__templateName":159},"Become a Sponsor","2023-12-06T21:58:57.447Z","2023-12-08T00:18:29.346Z","2023-12-06T23:18:03.082Z","48",{"id":638,"url_path":639,"generated":138,"contenttype":151,"createdAt":640,"updatedAt":640},48,"/exhibitors-and-sponsors/become-a-sponsor","2023-12-06T21:58:57.454Z",{},{},[],{"id":288,"title":645,"menuAttached":8,"order":191,"path":646,"type":143,"uiRouterKey":647,"slug":648,"external":138,"related":649,"items":661},"On-Site Information","/useful-on-site-information","on-site-information","useful-on-site-information",{"id":638,"heading":650,"createdAt":651,"updatedAt":652,"publishedAt":653,"url_path_id":654,"__contentType":151,"pathAlias":655,"navigationItemId":288,"createdBy":659,"updatedBy":660,"__templateName":159},"Useful On-Site Information","2024-12-05T19:54:00.432Z","2024-12-17T08:17:00.182Z","2024-12-05T20:09:36.650Z","164",{"id":656,"url_path":646,"generated":8,"contenttype":151,"createdAt":657,"updatedAt":658},164,"2024-12-05T19:54:00.451Z","2024-12-17T08:17:00.220Z",{},{},[],{"data":16,"error":663},{"status":664,"name":665,"message":666,"details":667},404,"NotFoundError","Entity not found",{},{"affiliates":669},{"affiliates":670},{"data":671,"meta":1399},[672,717,762,806,851,897,925,971,1016,1056,1101,1139,1184,1231,1276,1319,1356],{"id":5,"name":673,"description":114,"createdAt":674,"updatedAt":675,"publishedAt":676,"url_path_id":677,"logo":678,"website":711,"url_path":716},"IEEE","2023-08-03T15:56:36.046Z","2023-08-03T15:56:38.008Z","2023-08-03T15:56:38.001Z","43",{"id":492,"name":679,"alternativeText":16,"caption":16,"width":680,"height":681,"formats":682,"hash":707,"ext":21,"mime":24,"size":708,"url":709,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":710,"updatedAt":710},"IEEE.png",2560,1439,{"large":683,"small":689,"medium":695,"thumbnail":701},{"ext":21,"url":684,"hash":685,"mime":24,"name":686,"path":16,"size":687,"width":28,"height":688},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_IEEE_e2e39b9dc2.png","large_IEEE_e2e39b9dc2","large_IEEE.png",145.48,562,{"ext":21,"url":690,"hash":691,"mime":24,"name":692,"path":16,"size":693,"width":35,"height":694},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_IEEE_e2e39b9dc2.png","small_IEEE_e2e39b9dc2","small_IEEE.png",54.62,281,{"ext":21,"url":696,"hash":697,"mime":24,"name":698,"path":16,"size":699,"width":42,"height":700},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_IEEE_e2e39b9dc2.png","medium_IEEE_e2e39b9dc2","medium_IEEE.png",97.44,422,{"ext":21,"url":702,"hash":703,"mime":24,"name":704,"path":16,"size":705,"width":87,"height":706},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_IEEE_e2e39b9dc2.png","thumbnail_IEEE_e2e39b9dc2","thumbnail_IEEE.png",20.03,138,"IEEE_e2e39b9dc2",180.84,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/IEEE_e2e39b9dc2.png","2023-08-03T15:56:13.632Z",{"id":5,"variation":16,"button":712},[713],{"id":5,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":715,"newWindow":8,"downloadable":16,"shape":16},"More Info","https://www.ieee.org/","-21",{"id":110,"name":718,"description":114,"createdAt":719,"updatedAt":720,"publishedAt":721,"url_path_id":722,"logo":723,"website":757,"url_path":761},"IEEE Control System Society","2023-08-03T18:22:29.227Z","2023-08-03T18:22:32.960Z","2023-08-03T18:22:32.953Z","44",{"id":511,"name":724,"alternativeText":16,"caption":16,"width":725,"height":726,"formats":727,"hash":753,"ext":729,"mime":732,"size":754,"url":755,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":756,"updatedAt":756},"IEEE_CSS.jpeg",1479,851,{"large":728,"small":736,"medium":741,"thumbnail":747},{"ext":729,"url":730,"hash":731,"mime":732,"name":733,"path":16,"size":734,"width":28,"height":735},".jpeg","https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_IEEE_CSS_8ce7bb080f.jpeg","large_IEEE_CSS_8ce7bb080f","image/jpeg","large_IEEE_CSS.jpeg",51.75,575,{"ext":729,"url":737,"hash":738,"mime":732,"name":739,"path":16,"size":740,"width":35,"height":69},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_IEEE_CSS_8ce7bb080f.jpeg","small_IEEE_CSS_8ce7bb080f","small_IEEE_CSS.jpeg",21.26,{"ext":729,"url":742,"hash":743,"mime":732,"name":744,"path":16,"size":745,"width":42,"height":746},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_IEEE_CSS_8ce7bb080f.jpeg","medium_IEEE_CSS_8ce7bb080f","medium_IEEE_CSS.jpeg",36.24,432,{"ext":729,"url":748,"hash":749,"mime":732,"name":750,"path":16,"size":751,"width":87,"height":752},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_IEEE_CSS_8ce7bb080f.jpeg","thumbnail_IEEE_CSS_8ce7bb080f","thumbnail_IEEE_CSS.jpeg",7.44,141,"IEEE_CSS_8ce7bb080f",84.4,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/IEEE_CSS_8ce7bb080f.jpeg","2023-08-03T18:22:10.381Z",{"id":110,"variation":16,"button":758},[759],{"id":110,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":760,"newWindow":8,"downloadable":16,"shape":16},"https://www.ieeecss.org/","-22",{"id":168,"name":763,"description":114,"createdAt":764,"updatedAt":765,"publishedAt":766,"url_path_id":767,"logo":768,"website":801,"url_path":805},"EUCA","2023-08-03T18:23:18.342Z","2023-08-03T18:23:22.277Z","2023-08-03T18:23:22.267Z","45",{"id":583,"name":769,"alternativeText":16,"caption":16,"width":770,"height":771,"formats":772,"hash":797,"ext":21,"mime":24,"size":798,"url":799,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":800,"updatedAt":800},"EUCA.png",8894,6088,{"large":773,"small":779,"medium":785,"thumbnail":791},{"ext":21,"url":774,"hash":775,"mime":24,"name":776,"path":16,"size":777,"width":28,"height":778},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_EUCA_c95db1eef5.png","large_EUCA_c95db1eef5","large_EUCA.png",68.74,685,{"ext":21,"url":780,"hash":781,"mime":24,"name":782,"path":16,"size":783,"width":35,"height":784},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_EUCA_c95db1eef5.png","small_EUCA_c95db1eef5","small_EUCA.png",30.53,342,{"ext":21,"url":786,"hash":787,"mime":24,"name":788,"path":16,"size":789,"width":42,"height":790},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_EUCA_c95db1eef5.png","medium_EUCA_c95db1eef5","medium_EUCA.png",49.19,513,{"ext":21,"url":792,"hash":793,"mime":24,"name":794,"path":16,"size":795,"width":796,"height":49},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_EUCA_c95db1eef5.png","thumbnail_EUCA_c95db1eef5","thumbnail_EUCA.png",11.9,228,"EUCA_c95db1eef5",701.69,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/EUCA_c95db1eef5.png","2023-08-03T18:22:55.236Z",{"id":168,"variation":16,"button":802},[803],{"id":168,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":804,"newWindow":8,"downloadable":16,"shape":16},"https://euca-ecc.org/","-23",{"id":14,"name":807,"description":114,"createdAt":808,"updatedAt":809,"publishedAt":810,"url_path_id":811,"logo":812,"website":846,"url_path":850},"SICE","2023-08-03T18:25:22.738Z","2023-08-03T23:01:45.675Z","2023-08-03T18:25:24.406Z","46",{"id":263,"name":813,"alternativeText":16,"caption":16,"width":814,"height":815,"formats":816,"hash":842,"ext":818,"mime":732,"size":843,"url":844,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":845,"updatedAt":845},"SICE.jpg",2036,525,{"large":817,"small":824,"medium":830,"thumbnail":836},{"ext":818,"url":819,"hash":820,"mime":732,"name":821,"path":16,"size":822,"width":28,"height":823},".jpg","https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_SICE_04fd935af7.jpg","large_SICE_04fd935af7","large_SICE.jpg",14.85,258,{"ext":818,"url":825,"hash":826,"mime":732,"name":827,"path":16,"size":828,"width":35,"height":829},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_SICE_04fd935af7.jpg","small_SICE_04fd935af7","small_SICE.jpg",6.92,129,{"ext":818,"url":831,"hash":832,"mime":732,"name":833,"path":16,"size":834,"width":42,"height":835},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_SICE_04fd935af7.jpg","medium_SICE_04fd935af7","medium_SICE.jpg",10.6,193,{"ext":818,"url":837,"hash":838,"mime":732,"name":839,"path":16,"size":840,"width":87,"height":841},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_SICE_04fd935af7.jpg","thumbnail_SICE_04fd935af7","thumbnail_SICE.jpg",3.46,63,"SICE_04fd935af7",32.55,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/SICE_04fd935af7.jpg","2023-08-03T18:24:19.020Z",{"id":14,"variation":16,"button":847},[848],{"id":14,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":849,"newWindow":8,"downloadable":16,"shape":16},"https://www.sice.jp/english/","-24",{"id":153,"name":852,"description":853,"createdAt":854,"updatedAt":855,"publishedAt":856,"url_path_id":857,"logo":858,"website":892,"url_path":896},"BUDD-e","\u003Cp>\u003Cspan style=\"color:#434343;\">A systematic review conducted in 2020 identified the number of blind and visually impaired people in the world: of the 7.79 billion people living on earth, 49.1 million were totally blind, 33.6 million had severe vision problems and 221.4 million had moderate vision problems. Due to an aging population, it is estimated that the rate of people affected by vision problems will continue to increase in the coming decades.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">One of the major problems for visually impaired people is the difficulty of navigating in unfamiliar environments. This creates barriers and inequalities, e.g., in accessing buildings and services and in participating in sports. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">The use of traditional assistive devices can be problematic. For example, relying solely on the white cane does not solve a solution to the autonomy problem; additionally, some visually impaired individuals may experience unfavorable emotions when using such a tool. Also, guide dogs require attention from the users and, even if they are well trained, they can't be left alone for a long time. In addition, assistance dogs are often denied access to many public spaces.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">This highlights the need to provide novel solutions that, on the one hand, can guarantee assistance to visually impaired people and, on the other hand, can contribute to simplifying the role of caregivers, e.g., through the development of appropriate and dedicated technological assistive tools. In this project we have designed and realized a first prototype of the innovative autonomous robotic guide BUDD-e for blind and visually impaired persons, endowed with an innovative human-robot interface.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">Experimental validation tests have been conducted in healthcare facilities (ASST Grande Ospedale Metropolitano Niguarda) and are currently conducted in sport centers (Centro Sportivo Giuriati, Milano). This work is carried out in the framework of the project BUDD-e, funded by the Politecnico di Milano (in particular by the Polisocial Award 2021, the initiative of the Politecnico di Milano to support research projects focused on social commitment) and by the Italian MUR PRIN 2022 project \"Control of Assistive Robots in crowded Environments\" (CARE, Id. 20225LX9M3). \u003C/span>\u003C/p>","2024-07-26T04:43:12.714Z","2024-07-31T09:26:02.674Z","2024-07-26T04:43:14.278Z","115",{"id":859,"name":860,"alternativeText":16,"caption":16,"width":861,"height":862,"formats":863,"hash":888,"ext":21,"mime":24,"size":889,"url":890,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":891,"updatedAt":891},83,"Budd-e.png",2048,986,{"large":864,"small":870,"medium":876,"thumbnail":882},{"ext":21,"url":865,"hash":866,"mime":24,"name":867,"path":16,"size":868,"width":28,"height":869},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_Budd_e_1d8b4119fd.png","large_Budd_e_1d8b4119fd","large_Budd-e.png",93.38,481,{"ext":21,"url":871,"hash":872,"mime":24,"name":873,"path":16,"size":874,"width":35,"height":875},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_Budd_e_1d8b4119fd.png","small_Budd_e_1d8b4119fd","small_Budd-e.png",42.69,241,{"ext":21,"url":877,"hash":878,"mime":24,"name":879,"path":16,"size":880,"width":42,"height":881},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_Budd_e_1d8b4119fd.png","medium_Budd_e_1d8b4119fd","medium_Budd-e.png",66.78,361,{"ext":21,"url":883,"hash":884,"mime":24,"name":885,"path":16,"size":886,"width":87,"height":887},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_Budd_e_1d8b4119fd.png","thumbnail_Budd_e_1d8b4119fd","thumbnail_Budd-e.png",16.88,118,"Budd_e_1d8b4119fd",30.82,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/Budd_e_1d8b4119fd.png","2024-07-31T09:25:50.912Z",{"id":191,"variation":95,"button":893},[894],{"id":343,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":895,"newWindow":16,"downloadable":16,"shape":16},"https://budd-e.polimi.it/","-78",{"id":174,"name":898,"description":899,"createdAt":900,"updatedAt":901,"publishedAt":902,"url_path_id":903,"logo":904,"website":920,"url_path":924},"Mitsubishi Electric Research Laboratory (MERL)","\u003Cp>\u003Cspan style=\"color:#434343;\">Mitsubishi Electric Research Laboratories (MERL), located in Cambridge, MA, is the North American R&D organization for Mitsubishi Electric Corporation, a $40B global manufacturer of electrical products including elevator and escalators, HVAC systems, electrical power systems, satellites, factory automation equipment, automotive electronics and visual information systems. Controls researchers at MERL collaborate with corporate R&D laboratories, business units in Japan and the United States, and academic partners around the world to develop new control algorithms and control technologies that extend the capabilities and the performance envelope of these systems.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">For students who are interested in pursuing an exciting research internship, please check out our internship program and learn more on our Website, Facebook, LinkedIn or @MERL_news.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">MERL interns work closely with top researchers, and gain valuable industry experience – at an impressive 1:1 intern to researcher ratio. Internships are expected to lead to publications in major conferences and journals. We also recently started a PostDoc program. See our website\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"http://www.merl.com/\">\u003Cspan style=\"color:#434343;\"> \u003Cu>www.merl.com\u003C/u>\u003C/span>\u003C/a>\u003Cspan style=\"color:#434343;\"> for application procedures.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">We offer competitive compensation and relocation assistance. Boston is a fantastic student-oriented city, home to some of the best universities in the world.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">The summer season is especially lively as MERL and Boston are teeming with researchers and visitors from all over the world.\u003C/span>\u003C/p>","2024-07-31T09:06:22.714Z","2024-07-31T09:18:18.648Z","2024-07-31T09:10:16.665Z","124",{"id":905,"name":906,"alternativeText":16,"caption":16,"width":907,"height":908,"formats":909,"hash":916,"ext":818,"mime":732,"size":917,"url":918,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":919,"updatedAt":919},79,"MitsubishiElectric_LogoOfficial.jpg",466,204,{"thumbnail":910},{"ext":818,"url":911,"hash":912,"mime":732,"name":913,"path":16,"size":914,"width":87,"height":915},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_Mitsubishi_Electric_Logo_Official_f76352ac96.jpg","thumbnail_Mitsubishi_Electric_Logo_Official_f76352ac96","thumbnail_MitsubishiElectric_LogoOfficial.jpg",7.33,107,"Mitsubishi_Electric_Logo_Official_f76352ac96",16.87,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/Mitsubishi_Electric_Logo_Official_f76352ac96.jpg","2024-07-31T09:08:03.564Z",{"id":208,"variation":95,"button":921},[922],{"id":191,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":923,"newWindow":16,"downloadable":16,"shape":16},"https://www.merl.com","-83",{"id":191,"name":926,"description":927,"createdAt":928,"updatedAt":929,"publishedAt":930,"url_path_id":931,"logo":932,"website":966,"url_path":970},"MathWorks","\u003Cp>\u003Cspan style=\"color:#434343;\">The MATLAB and Simulink product families are fundamental applied math and computational tools at the world's educational institutions. Adopted by more than 6,500 universities and colleges, MathWorks products accelerate the pace of learning, teaching, and research in engineering and science. MathWorks products also help prepare students for careers in industry worldwide, where the tools are widely used for data analysis, mathematical modeling, and algorithm development in collaborative research and new product development. Application areas include data analytics, mechatronics, communication systems, image processing, computational finance, and computational biology.\u003C/span>\u003C/p>","2024-07-31T09:11:57.520Z","2024-07-31T09:18:53.370Z","2024-07-31T09:14:51.843Z","125",{"id":933,"name":934,"alternativeText":16,"caption":16,"width":935,"height":936,"formats":937,"hash":962,"ext":21,"mime":24,"size":963,"url":964,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":965,"updatedAt":965},80,"09_MW_logo_RGB_transparent.png",2460,489,{"large":938,"small":944,"medium":950,"thumbnail":956},{"ext":21,"url":939,"hash":940,"mime":24,"name":941,"path":16,"size":942,"width":28,"height":943},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_09_MW_logo_RGB_transparent_658a0d0d93.png","large_09_MW_logo_RGB_transparent_658a0d0d93","large_09_MW_logo_RGB_transparent.png",72,199,{"ext":21,"url":945,"hash":946,"mime":24,"name":947,"path":16,"size":948,"width":35,"height":949},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_09_MW_logo_RGB_transparent_658a0d0d93.png","small_09_MW_logo_RGB_transparent_658a0d0d93","small_09_MW_logo_RGB_transparent.png",28.85,99,{"ext":21,"url":951,"hash":952,"mime":24,"name":953,"path":16,"size":954,"width":42,"height":955},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_09_MW_logo_RGB_transparent_658a0d0d93.png","medium_09_MW_logo_RGB_transparent_658a0d0d93","medium_09_MW_logo_RGB_transparent.png",47.66,149,{"ext":21,"url":957,"hash":958,"mime":24,"name":959,"path":16,"size":960,"width":87,"height":961},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_09_MW_logo_RGB_transparent_658a0d0d93.png","thumbnail_09_MW_logo_RGB_transparent_658a0d0d93","thumbnail_09_MW_logo_RGB_transparent.png",11.16,49,"09_MW_logo_RGB_transparent_658a0d0d93",42.27,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/09_MW_logo_RGB_transparent_658a0d0d93.png","2024-07-31T09:14:28.590Z",{"id":116,"variation":95,"button":967},[968],{"id":208,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":969,"newWindow":16,"downloadable":16,"shape":16},"https://www.mathworks.com/","-84",{"id":208,"name":972,"description":973,"createdAt":974,"updatedAt":975,"publishedAt":976,"url_path_id":977,"logo":978,"website":1011,"url_path":1015},"Springer","\u003Cp>\u003Cspan style=\"color:#434343;\">Springer is a leading global scientific, technical and medical portfolio, providing researchers in academia, scientific institutions and corporate R&D departments with quality content through innovative information, products and services. Springer has one of the strongest STM and HSS eBook collections and archives, as well as a comprehensive range of hybrid and open access journals. Springer is part of Springer Nature, a global publisher that serves and supports the research community. Springer Nature aims to advance discovery by publishing robust and insightful science, supporting the development of new areas of research and making ideas and knowledge accessible around the world.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">As part of Springer Nature, Springer sits alongside other trusted brands like Nature Portfolio, BMC and Palgrave Macmillan. Visit\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"http://www.springer.com/\">\u003Cspan style=\"color:#434343;\"> \u003Cu>springer.com\u003C/u>\u003C/span>\u003C/a>\u003Cspan style=\"color:#434343;\"> and follow\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://twitter.com/springernature\">\u003Cspan style=\"color:#434343;\"> \u003Cu>@SpringerNature\u003C/u>\u003C/span>\u003C/a>\u003Cspan style=\"color:#434343;\">.\u003C/span>\u003C/p>","2024-07-31T09:19:24.410Z","2024-07-31T09:31:27.755Z","2024-07-31T09:21:44.962Z","126",{"id":979,"name":980,"alternativeText":16,"caption":16,"width":981,"height":982,"formats":983,"hash":1007,"ext":21,"mime":24,"size":1008,"url":1009,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1010,"updatedAt":1010},82,"Springer logo.png",1200,900,{"large":984,"small":989,"medium":995,"thumbnail":1001},{"ext":21,"url":985,"hash":986,"mime":24,"name":987,"path":16,"size":988,"width":28,"height":42},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_Springer_logo_6100b36081.png","large_Springer_logo_6100b36081","large_Springer logo.png",72.56,{"ext":21,"url":990,"hash":991,"mime":24,"name":992,"path":16,"size":993,"width":35,"height":994},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_Springer_logo_6100b36081.png","small_Springer_logo_6100b36081","small_Springer logo.png",23.85,375,{"ext":21,"url":996,"hash":997,"mime":24,"name":998,"path":16,"size":999,"width":42,"height":1000},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_Springer_logo_6100b36081.png","medium_Springer_logo_6100b36081","medium_Springer logo.png",44.53,563,{"ext":21,"url":1002,"hash":1003,"mime":24,"name":1004,"path":16,"size":1005,"width":1006,"height":49},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_Springer_logo_6100b36081.png","thumbnail_Springer_logo_6100b36081","thumbnail_Springer logo.png",6.2,208,"Springer_logo_6100b36081",23.24,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/Springer_logo_6100b36081.png","2024-07-31T09:23:02.499Z",{"id":330,"variation":95,"button":1012},[1013],{"id":330,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1014,"newWindow":16,"downloadable":16,"shape":16},"https://www.springer.com","-77",{"id":116,"name":1017,"description":1018,"createdAt":1019,"updatedAt":1020,"publishedAt":1021,"url_path_id":1022,"logo":1023,"website":1051,"url_path":1055},"ANT-X","\u003Cp>\u003Cspan style=\"color:#434343;\">ANT-X is a spin-off company of Politecnico di Milano. It was founded in early 2020 on the basis of the experience gained by its co-founders within the Aerospace Systems and Control Laboratory of the Department of Aerospace Science and Technology.\u003C/span>\u003Cbr>\u003Cbr>\u003Cspan style=\"color:#434343;\">ANT-X provides laboratory solutions for research and education in multi-agent systems, flight robotics, flight control and aerospace control. The ANT-X educational drones are designed for students and researchers, to enable transition from theory to practice of advanced design methods for guidance, navigation, and control systems. They are based on open-source software and allow the user to customize the drone platform to implement, simulate, and flight test novel guidance and control algorithms. This enriches the experience in flight robotics and UAV control through hands-on experimental activities.\u003C/span>\u003Cbr>\u003Cspan style=\"color:#434343;\">Based on the experience gathered through the years in research and education about guidance, navigation and control of UAVs, ANT-X can provide educational material as a support to lecturers, based on state-of-the-art analysis and design methods. The ANT-X laboratory solutions are designed focusing on the need for ready to use and customizable platforms for research and education.\u003C/span>\u003Cbr>\u003Cbr>\u003Cspan style=\"color:#434343;\">In addition, ANT-X designs and builds custom drone solutions tailored to specific industrial applications.\u003C/span>\u003Cbr>\u003Cspan style=\"color:#434343;\">Based on the experience gathered as a university laboratory in the research area of guidance, navigation and control of UAVs, ANT-X has the competences needed to carry out the entire process of design, prototyping, integration, and flight testing of custom UAV platforms both for scientific research and for industrial applications.\u003C/span>\u003C/p>","2024-07-31T22:58:56.930Z","2024-08-03T01:22:14.958Z","2024-07-31T23:03:29.185Z","127",{"id":1024,"name":1025,"alternativeText":16,"caption":16,"width":1026,"height":1027,"formats":1028,"hash":1047,"ext":21,"mime":24,"size":1048,"url":1049,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1050,"updatedAt":1050},84,"ANT-X_positivo-verticale.png",827,713,{"small":1029,"medium":1035,"thumbnail":1041},{"ext":21,"url":1030,"hash":1031,"mime":24,"name":1032,"path":16,"size":1033,"width":35,"height":1034},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_ANT_X_positivo_verticale_f824d784a8.png","small_ANT_X_positivo_verticale_f824d784a8","small_ANT-X_positivo-verticale.png",54.14,431,{"ext":21,"url":1036,"hash":1037,"mime":24,"name":1038,"path":16,"size":1039,"width":42,"height":1040},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_ANT_X_positivo_verticale_f824d784a8.png","medium_ANT_X_positivo_verticale_f824d784a8","medium_ANT-X_positivo-verticale.png",102.91,647,{"ext":21,"url":1042,"hash":1043,"mime":24,"name":1044,"path":16,"size":1045,"width":1046,"height":49},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_ANT_X_positivo_verticale_f824d784a8.png","thumbnail_ANT_X_positivo_verticale_f824d784a8","thumbnail_ANT-X_positivo-verticale.png",13.92,181,"ANT_X_positivo_verticale_f824d784a8",17.03,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/ANT_X_positivo_verticale_f824d784a8.png","2024-07-31T22:59:33.086Z",{"id":343,"variation":95,"button":1052},[1053],{"id":354,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1054,"newWindow":16,"downloadable":16,"shape":16},"https://antx.it/","-85",{"id":330,"name":1057,"description":1058,"createdAt":1059,"updatedAt":1060,"publishedAt":1061,"url_path_id":1062,"logo":1063,"website":1096,"url_path":1100},"The Franklin Institute","\u003Cp>\u003Cspan style=\"color:#434343;\">Franklin Open is a peer-reviewed, gold open-access journal that focuses on the fields of engineering and applied mathematics. As a partner journal to the longstanding Journal of The Franklin Institute, which has been publishing scientific research and discoveries for almost 200 years, Franklin Open was created to not only continue that legacy, but to provide a sustainable platform for new research to be widely disseminated from all voices in the scientific and academic communities. Franklin Open aims to publish high-quality manuscripts under such topics as, Complex Networks & Cyber-Physical Systems, Control Engineering & Robotics, Energy & Power Systems, Information & Communications, Data Science & Artificial Intelligence, Neural Networks & Learning Systems, and Speech, Image, & Signal Processing. We welcome new submissions as well as special issue proposals through our website. If you have any questions, please contact \u003C/span>\u003Ca href=\"mailto:franklinopen@fi.edu\">\u003Cspan style=\"color:#1155cc;\">\u003Cu>franklinopen@fi.edu\u003C/u>\u003C/span>\u003C/a>\u003Cspan style=\"color:#434343;\">.\u003C/span>\u003C/p>","2024-07-31T23:01:06.473Z","2024-08-27T01:01:11.876Z","2024-07-31T23:02:13.315Z","128",{"id":1064,"name":1065,"alternativeText":16,"caption":16,"width":1066,"height":1067,"formats":1068,"hash":1092,"ext":818,"mime":732,"size":1093,"url":1094,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1095,"updatedAt":1095},85,"Franklin Open Title.jpg",2480,688,{"large":1069,"small":1075,"medium":1081,"thumbnail":1086},{"ext":818,"url":1070,"hash":1071,"mime":732,"name":1072,"path":16,"size":1073,"width":28,"height":1074},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_Franklin_Open_Title_fab202c8f6.jpg","large_Franklin_Open_Title_fab202c8f6","large_Franklin Open Title.jpg",28.72,277,{"ext":818,"url":1076,"hash":1077,"mime":732,"name":1078,"path":16,"size":1079,"width":35,"height":1080},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_Franklin_Open_Title_fab202c8f6.jpg","small_Franklin_Open_Title_fab202c8f6","small_Franklin Open Title.jpg",11.2,139,{"ext":818,"url":1082,"hash":1083,"mime":732,"name":1084,"path":16,"size":1085,"width":42,"height":1006},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_Franklin_Open_Title_fab202c8f6.jpg","medium_Franklin_Open_Title_fab202c8f6","medium_Franklin Open Title.jpg",19.7,{"ext":818,"url":1087,"hash":1088,"mime":732,"name":1089,"path":16,"size":1090,"width":87,"height":1091},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_Franklin_Open_Title_fab202c8f6.jpg","thumbnail_Franklin_Open_Title_fab202c8f6","thumbnail_Franklin Open Title.jpg",4.23,68,"Franklin_Open_Title_fab202c8f6",81.38,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/Franklin_Open_Title_fab202c8f6.jpg","2024-07-31T23:02:05.739Z",{"id":354,"variation":95,"button":1097},[1098],{"id":396,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1099,"newWindow":16,"downloadable":16,"shape":16},"https://www.sciencedirect.com/journal/franklin-open","-86",{"id":343,"name":1102,"description":1103,"createdAt":1104,"updatedAt":1105,"publishedAt":1106,"url_path_id":1107,"logo":1108,"website":1134,"url_path":1138},"AIDA – Artificial Intelligence Driving Autonomous","\u003Cp>\u003Cstrong>Schedule:\u003C/strong> Monday 16 - Friday 19\u003Cbr>\u003Cstrong>Location:\u003C/strong> Exhibition Area\u003C/p>\u003Cp>\u003Cspan style=\"color:#434343;\">AIDA (Artificial Intelligence Driving Autonomous) is an ambitious project by the Politecnico di Milano, aimed at experimenting with autonomous driving on public roads. Of particular importance was the participation in the 2023 and 2024 editions of the historic 1000 Miglia race and in the Trofeo Vallecamonica, events that have allowed the system’s capabilities to be tested in highly demanding and competitive contexts. Simultaneously, numerous new tests will be launched in urban environments with the objective of evaluating the effectiveness and reliability of autonomous driving in real and complex traffic scenarios. The project aims to create a future where road safety and reliability are significantly improved. This approach not only promises to reduce accidents and increase safety for all road users but also to make mobility more efficient and sustainable. With the “AIDA” project, the Politecnico di Milano not only positions itself at the forefront of technological research but also commits to playing a key role in shaping the future of Italian mobility. The adoption of artificial intelligence in autonomous driving represents both a challenge and an opportunity to redefine the way we move, laying the foundations for a new era of innovation and progress in the transportation sector.\u003C/span>\u003C/p>","2024-08-01T22:48:20.917Z","2024-09-15T00:49:27.123Z","2024-08-01T22:55:34.748Z","129",{"id":1109,"name":1110,"alternativeText":16,"caption":16,"width":1111,"height":1112,"formats":1113,"hash":1130,"ext":21,"mime":24,"size":1131,"url":1132,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1133,"updatedAt":1133},87,"logo_AIDA.png",969,161,{"small":1114,"medium":1119,"thumbnail":1125},{"ext":21,"url":1115,"hash":1116,"mime":24,"name":1117,"path":16,"size":1118,"width":35,"height":859},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_logo_AIDA_5487aa62d5.png","small_logo_AIDA_5487aa62d5","small_logo_AIDA.png",30.64,{"ext":21,"url":1120,"hash":1121,"mime":24,"name":1122,"path":16,"size":1123,"width":42,"height":1124},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_logo_AIDA_5487aa62d5.png","medium_logo_AIDA_5487aa62d5","medium_logo_AIDA.png",53.44,125,{"ext":21,"url":1126,"hash":1127,"mime":24,"name":1128,"path":16,"size":1129,"width":87,"height":437},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_logo_AIDA_5487aa62d5.png","thumbnail_logo_AIDA_5487aa62d5","thumbnail_logo_AIDA.png",11.21,"logo_AIDA_5487aa62d5",12.66,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/logo_AIDA_5487aa62d5.png","2024-08-01T22:59:58.209Z",{"id":396,"variation":95,"button":1135},[1136],{"id":406,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1137,"newWindow":16,"downloadable":16,"shape":16},"https://1000mad.deib.polimi.it/en/","-87",{"id":354,"name":1140,"description":1141,"createdAt":1142,"updatedAt":1143,"publishedAt":1144,"url_path_id":1145,"logo":1146,"website":1178,"url_path":1183},"ANTHEM - AdvaNced Technology for Human centEred Medicine","\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"color:#434343;\">ANTHEM is a research initiative funded with 123 million euros by the Ministry of University and Research through the \"National Plan for complementary investments to the European Recovery and Resilience Plan. The research activities aim to introduce innovative technologies into diagnostic and therapeutic processes in healthcare to improve the quality of life of fragile and chronic patients or those affected by pathologies that are still without any therapy.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"color:#434343;\">ANTHEM involves 9 universities, 3 research centers, 6 large hospitals and 5 companies distributed across 7 Italian regions. The research activities are divided into four macro-areas called Spokes, each dedicated to specific pathologies and territorial communities in order to maximize and accelerate the impact of research on people. Researchers work on 28 pilot projects that aim to produce concrete effects in a short time. The mission is to quickly make new diagnostic tools and new therapies available to patients. For this reason, in some cases, we work on technologies already available in other technological fields, ready to be transferred to the medical field.\u003C/span>\u003C/p>","2024-08-03T01:23:11.235Z","2024-08-03T01:26:22.101Z","2024-08-03T01:26:22.082Z","130",{"id":1147,"name":1148,"alternativeText":16,"caption":16,"width":1149,"height":1150,"formats":1151,"hash":1174,"ext":21,"mime":24,"size":1175,"url":1176,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1177,"updatedAt":1177},88,"anthem final.png",2067,1670,{"large":1152,"small":1158,"medium":1163,"thumbnail":1169},{"ext":21,"url":1153,"hash":1154,"mime":24,"name":1155,"path":16,"size":1156,"width":28,"height":1157},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_anthem_final_92744e49e5.png","large_anthem_final_92744e49e5","large_anthem final.png",191.09,808,{"ext":21,"url":1159,"hash":1160,"mime":24,"name":1161,"path":16,"size":1162,"width":35,"height":664},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_anthem_final_92744e49e5.png","small_anthem_final_92744e49e5","small_anthem final.png",69.08,{"ext":21,"url":1164,"hash":1165,"mime":24,"name":1166,"path":16,"size":1167,"width":42,"height":1168},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_anthem_final_92744e49e5.png","medium_anthem_final_92744e49e5","medium_anthem final.png",123.37,606,{"ext":21,"url":1170,"hash":1171,"mime":24,"name":1172,"path":16,"size":1173,"width":835,"height":49},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_anthem_final_92744e49e5.png","thumbnail_anthem_final_92744e49e5","thumbnail_anthem final.png",18.8,"anthem_final_92744e49e5",122.89,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/anthem_final_92744e49e5.png","2024-08-03T01:24:55.508Z",{"id":406,"variation":95,"button":1179},[1180],{"id":1181,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1182,"newWindow":16,"downloadable":16,"shape":16},16,"https://fondazioneanthem.it/","-88",{"id":396,"name":1185,"description":1186,"createdAt":1187,"updatedAt":1188,"publishedAt":1189,"url_path_id":1190,"logo":1191,"website":1225,"url_path":1230},"MOST - National Center for Sustainable Mobility","\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"color:#434343;\">MOST – National Centre for Sustainable Mobility, through collaboration with 24 universities, National Research Center (CNR) and 24 large companies, has the mission of implementing modern, sustainable and inclusive solutions for the entire national territory. This research initiative is funded with 378 million euros by the Ministry of University and Research through the European Recovery and Resilience Plan (PNRR).\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"color:#434343;\">The areas and technological fields of greatest interest in the project are: air mobility, sustainable road vehicles, water transport, rail transport, light vehicles and active mobility. The National Center will take care of making the mobility system more \"green\" as a whole and more \"digital\" in its management. It will do so through lightweight solutions and electric and hydrogen propulsion systems; digital systems for the reduction of accidents; more effective solutions for public transport and logistics; a new model of mobility, as a service, accessible and inclusive.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"color:#434343;\">The Spoke 5 is devoted to Light and Active Mobility through the development of innovative solutions for vehicles and mobility systems.\u003C/span>\u003C/p>","2024-08-03T01:27:16.721Z","2024-08-03T01:31:30.211Z","2024-08-03T01:31:30.202Z","131",{"id":1192,"name":1193,"alternativeText":16,"caption":16,"width":1194,"height":1195,"formats":1196,"hash":1221,"ext":21,"mime":24,"size":1222,"url":1223,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1224,"updatedAt":1224},89,"most.png",2243,871,{"large":1197,"small":1203,"medium":1209,"thumbnail":1215},{"ext":21,"url":1198,"hash":1199,"mime":24,"name":1200,"path":16,"size":1201,"width":28,"height":1202},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_most_f4411a1d59.png","large_most_f4411a1d59","large_most.png",123.87,388,{"ext":21,"url":1204,"hash":1205,"mime":24,"name":1206,"path":16,"size":1207,"width":35,"height":1208},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_most_f4411a1d59.png","small_most_f4411a1d59","small_most.png",48.97,194,{"ext":21,"url":1210,"hash":1211,"mime":24,"name":1212,"path":16,"size":1213,"width":42,"height":1214},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_most_f4411a1d59.png","medium_most_f4411a1d59","medium_most.png",82.91,291,{"ext":21,"url":1216,"hash":1217,"mime":24,"name":1218,"path":16,"size":1219,"width":87,"height":1220},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_most_f4411a1d59.png","thumbnail_most_f4411a1d59","thumbnail_most.png",19.14,95,"most_f4411a1d59",74.6,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/most_f4411a1d59.png","2024-08-03T01:31:14.450Z",{"id":1181,"variation":95,"button":1226},[1227],{"id":1228,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1229,"newWindow":16,"downloadable":16,"shape":16},17,"https://www.centronazionalemost.it/eg/","-89",{"id":406,"name":1232,"description":1233,"createdAt":1234,"updatedAt":1235,"publishedAt":1236,"url_path_id":1237,"logo":1238,"website":1270,"url_path":1275},"SIAM","\u003Cp style=\"text-align:justify;\">The Society for Industrial and Applied Mathematics (SIAM) is an international society of over 12,000+ members from 85 countries. Browse the books, including those in the Advances in Design and Control book series, and take advantage of the conference discount. Thinking of writing a book? Talk to Executive Editor Elizabeth Greenspan.\u003C/p>","2024-08-13T22:11:48.414Z","2024-09-14T23:31:22.364Z","2024-08-13T22:16:35.500Z","135",{"id":1239,"name":1240,"alternativeText":16,"caption":16,"width":1241,"height":81,"formats":1242,"hash":1266,"ext":21,"mime":24,"size":1267,"url":1268,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1269,"updatedAt":1269},91,"siam.png",1441,{"large":1243,"small":1249,"medium":1255,"thumbnail":1261},{"ext":21,"url":1244,"hash":1245,"mime":24,"name":1246,"path":16,"size":1247,"width":28,"height":1248},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_siam_31b19fa32a.png","large_siam_31b19fa32a","large_siam.png",75.17,150,{"ext":21,"url":1250,"hash":1251,"mime":24,"name":1252,"path":16,"size":1253,"width":35,"height":1254},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_siam_31b19fa32a.png","small_siam_31b19fa32a","small_siam.png",24.6,75,{"ext":21,"url":1256,"hash":1257,"mime":24,"name":1258,"path":16,"size":1259,"width":42,"height":1260},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_siam_31b19fa32a.png","medium_siam_31b19fa32a","medium_siam.png",47.07,112,{"ext":21,"url":1262,"hash":1263,"mime":24,"name":1264,"path":16,"size":1265,"width":87,"height":366},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_siam_31b19fa32a.png","thumbnail_siam_31b19fa32a","thumbnail_siam.png",8.57,"siam_31b19fa32a",35.84,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/siam_31b19fa32a.png","2024-08-27T22:12:36.541Z",{"id":1228,"variation":95,"button":1271},[1272],{"id":1273,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1274,"newWindow":16,"downloadable":16,"shape":16},18,"https://www.siam.org/","-91",{"id":1181,"name":1277,"description":1278,"createdAt":1279,"updatedAt":1280,"publishedAt":1281,"url_path_id":1282,"logo":1283,"website":1314,"url_path":1318},"QUANSER","\u003Cp>Transforming engineering educational for over 35 years, Quanser has pioneered an interdisciplinary ecosystem that seamlessly integrates theory with practical applications. Our foundation, built on deep academic partnerships, empowers educators with cutting-edge solutions and innovative pedagogy tools like experiential learning and digital twinning. This ensures students develop in-demand skills for constantly evolving industries, and inspires insightful discovery for future research.\u003C/p>\u003Cp>With multidisciplinary and turnkey solutions spanning control, mechatronics, robotics, autonomous systems and applied AI, Quanser offers scalable and customizable platforms that are reliable, repeatable, and robust enough to last for generations of students. We are committed to accelerating research and maximizing academic investment, enabling over 2500 universities to inspire the next wave of engineering innovation. \u003C/p>","2024-09-14T23:33:24.667Z","2024-09-14T23:35:50.313Z","2024-09-14T23:35:50.306Z","145",{"id":1284,"name":1285,"alternativeText":16,"caption":16,"width":1286,"height":1287,"formats":1288,"hash":1310,"ext":818,"mime":732,"size":1311,"url":1312,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1313,"updatedAt":1313},92,"quanser.jpg",6400,959,{"large":1289,"small":1294,"medium":1300,"thumbnail":1305},{"ext":818,"url":1290,"hash":1291,"mime":732,"name":1292,"path":16,"size":1293,"width":28,"height":955},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_quanser_a2ce8343b2.jpg","large_quanser_a2ce8343b2","large_quanser.jpg",16.36,{"ext":818,"url":1295,"hash":1296,"mime":732,"name":1297,"path":16,"size":1298,"width":35,"height":1299},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_quanser_a2ce8343b2.jpg","small_quanser_a2ce8343b2","small_quanser.jpg",7.78,74,{"ext":818,"url":1301,"hash":1302,"mime":732,"name":1303,"path":16,"size":1304,"width":42,"height":1260},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_quanser_a2ce8343b2.jpg","medium_quanser_a2ce8343b2","medium_quanser.jpg",12.31,{"ext":818,"url":1306,"hash":1307,"mime":732,"name":1308,"path":16,"size":1309,"width":87,"height":320},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_quanser_a2ce8343b2.jpg","thumbnail_quanser_a2ce8343b2","thumbnail_quanser.jpg",3.25,"quanser_a2ce8343b2",135.81,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/quanser_a2ce8343b2.jpg","2024-09-14T23:35:34.468Z",{"id":1273,"variation":95,"button":1315},[1316],{"id":602,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1317,"newWindow":16,"downloadable":16,"shape":16},"https://www.quanser.com","-99",{"id":1228,"name":1320,"description":1321,"createdAt":1322,"updatedAt":1323,"publishedAt":1324,"url_path_id":1325,"logo":1326,"website":1351,"url_path":1355},"IIT Bombay","\u003Cp>\u003Cspan style=\"color:#434343;\">The Centre for Systems and Control (SysCon) is an interdisciplinary research group at IIT Bombay. Created in 1977 with the vision of pooling expertise from diverse areas to solve challenging engineering problems, the group has upheld the vision of its creators since its inception. The faculty members of SysCon are engineers and applied mathematicians having varied research backgrounds spanning almost all of the conventional domains of dynamical systems and control theory through the emerging application areas of quantum control and information, robotics, space systems, interconnected complex systems, flexible structures, games, numerical methods, signal processing, and financial networks. SysCon has an outstanding publication record at the top venues, a high density of students who have secured prestigious scholarships, and a rapid rate of developing new patentable technologies.\u003C/span>\u003C/p>","2024-11-07T21:17:53.744Z","2024-11-07T22:04:51.783Z","2024-11-07T22:04:51.776Z","159",{"id":619,"name":1327,"alternativeText":16,"caption":16,"width":1328,"height":943,"formats":1329,"hash":1347,"ext":21,"mime":24,"size":1348,"url":1349,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1350,"updatedAt":1350},"IITB.png",948,{"small":1330,"medium":1336,"thumbnail":1342},{"ext":21,"url":1331,"hash":1332,"mime":24,"name":1333,"path":16,"size":1334,"width":35,"height":1335},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_IITB_ea082123cc.png","small_IITB_ea082123cc","small_IITB.png",57.35,105,{"ext":21,"url":1337,"hash":1338,"mime":24,"name":1339,"path":16,"size":1340,"width":42,"height":1341},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_IITB_ea082123cc.png","medium_IITB_ea082123cc","medium_IITB.png",118.9,157,{"ext":21,"url":1343,"hash":1344,"mime":24,"name":1345,"path":16,"size":1346,"width":87,"height":504},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_IITB_ea082123cc.png","thumbnail_IITB_ea082123cc","thumbnail_IITB.png",16.71,"IITB_ea082123cc",66.1,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/IITB_ea082123cc.png","2024-11-07T22:04:28.431Z",{"id":602,"variation":95,"button":1352},[1353],{"id":383,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1354,"newWindow":16,"downloadable":16,"shape":16},"https://www.sc.iitb.ac.in","-111",{"id":1273,"name":1357,"description":1358,"createdAt":1359,"updatedAt":1360,"publishedAt":1361,"url_path_id":1362,"logo":1363,"website":1394,"url_path":1398},"Zhejiang University","\u003Cp>Zhejiang University ranks among world’s top 50 universities in QS World University Rankings and world’s top 20 universities in Automation & Control in Shanghai Ranking. It is located in Hangzhou, China.\u003C/p>\u003Cp>College of Control Science and Engineering (CSE), Zhejiang University was founded in 1956. For more than 60 years, CSE has been focusing on basic research and original innovation, aiming for the frontiers of science and technology. CSE is currently one of the most prestigious research and education bases in the area of industrial process control in China.\u003C/p>\u003Cp>CSE consists of five research institutes i.e. the Industrial Process Control, Smart Sensing and Measurement, Cyber-Systems and Control, Industry Intelligence and Systems Engineering, and Control Equipment and Comprehensive Safety. It offers undergraduate programs “Automation” and “Robot Engineering” and graduate programs “Control Science and Engineering” and “Electronic Information”. CSE also houses the State Key Laboratory of Industrial Control Technology, National Engineering Research Center of Industrial Automation, National Engineering Laboratory for Security Technology of Industrial Control System, National Center for International Research (Quality-targeted Process Optimization and Control).\u003C/p>","2024-11-18T12:48:33.183Z","2024-11-22T23:59:51.886Z","2024-11-18T12:52:11.071Z","161",{"id":372,"name":1364,"alternativeText":16,"caption":16,"width":1365,"height":664,"formats":1366,"hash":1389,"ext":21,"mime":24,"size":1390,"url":1391,"previewUrl":16,"provider":53,"provider_metadata":16,"createdAt":1392,"updatedAt":1393},"zhejiang.png",1842,{"large":1367,"small":1373,"medium":1379,"thumbnail":1384},{"ext":21,"url":1368,"hash":1369,"mime":24,"name":1370,"path":16,"size":1371,"width":28,"height":1372},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/large_zhejiang_4530ea3bb4.png","large_zhejiang_4530ea3bb4","large_zhejiang.png",66.34,219,{"ext":21,"url":1374,"hash":1375,"mime":24,"name":1376,"path":16,"size":1377,"width":35,"height":1378},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/small_zhejiang_4530ea3bb4.png","small_zhejiang_4530ea3bb4","small_zhejiang.png",25.48,110,{"ext":21,"url":1380,"hash":1381,"mime":24,"name":1382,"path":16,"size":1383,"width":42,"height":656},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/medium_zhejiang_4530ea3bb4.png","medium_zhejiang_4530ea3bb4","medium_zhejiang.png",44.82,{"ext":21,"url":1385,"hash":1386,"mime":24,"name":1387,"path":16,"size":1388,"width":87,"height":559},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/thumbnail_zhejiang_4530ea3bb4.png","thumbnail_zhejiang_4530ea3bb4","thumbnail_zhejiang.png",9.51,"zhejiang_4530ea3bb4",30.47,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/cdc24/zhejiang_4530ea3bb4.png","2024-11-18T12:51:13.815Z","2024-11-22T23:59:33.428Z",{"id":383,"variation":95,"button":1395},[1396],{"id":94,"label":714,"size":100,"color":101,"style":16,"icon":102,"iconPosition":103,"url":1397,"newWindow":16,"downloadable":16,"shape":16},"https://www.zju.edu.cn/english","-113",{"pagination":1400},{"page":5,"pageSize":517,"pageCount":5,"total":1228},{"id":250,"heading":251,"pageHeader":1402,"sections":1403},{"id":263,"description":16,"showPageHeader":8,"backgroundColor":118,"image":16},[1404,1409],{"id":638,"__component":1405,"componentVariation":1406,"styles":16,"header":16,"body":1407},"content.content","Content Image Left",{"id":638,"title":16,"body":1408,"containerWidth":16,"buttonGroup":16,"media":16},"\u003Cp>The 63rd IEEE CDC will be preceded by full-day workshops on Sunday, December 15, 2024, addressing current and future topics in control systems presented by experts from academia, research institutes, and industry. \u003C/p>\u003Cp>The workshops will be offered based on viable attendance. The 63rd CDC reserves the right to cancel nonviable workshops.\u003C/p>\u003Cp>Questions can be directed to the \u003Cstrong>workshop chair Hyungbo Shim\u003C/strong> (\u003Ca href=\"mailto:hshim@snu.ac.kr\">hshim@snu.ac.kr\u003C/a>).\u003C/p>",{"id":110,"__component":1410,"componentVariation":1411,"contactsVariation":1412,"styles":16,"header":1413,"sessionsGroup":1416},"content.sessions","Sessions Sidebar Navigation","Card Contact Full",{"id":1414,"heading":16,"prose":114,"lead":16,"eyebrow":16,"badge":16,"componentVariation":1415,"containerWidth":16,"image":16},50,"Heading Center",[1417],{"id":110,"groupTitle":16,"sessions":1418},[1419,1430,1441,1452,1463,1474,1485,1496,1507,1518,1529,1540,1551,1562,1573,1584,1595],{"id":208,"session":1420},{"id":208,"title":1421,"teaser":1422,"body":1423,"createdAt":1424,"updatedAt":1425,"publishedAt":1426,"url_path_id":1427,"contacts":1428,"url_path":1429},"Workshop 1: Contraction Theory for Systems, Control, Optimization, and Learning","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizer\u003C/strong>: Francesco Bullo* (University of California Santa Barbara)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers\u003C/strong> (in alphabetical order): Zahra Aminzare (University of Iowa), David Angeli (Imperial College), Daniele Astolfi (Université de Lyon), Francesco Bullo (UC Santa Barbara), Emiliano Dall'Anese (Boston University), Peter Giesl (University of Sussex), Yu Kawano (Hiroshima University), Ian Manchester (University of Sydney), Michael Margaliot (Tel Aviv University), Anton Proskurnikov (Politecnico di Torino), Giovanni Russo (Universita di Salerno), Rodolphe Sepulchre (Cambridge University), Jean-Jacques Slotine (MIT), Eduardo Sontag (NorthEastern University)\u003C/span>\u003C/p>\u003Cp>\u003Cstrong>Location: \u003C/strong>Amber 1 (Floor 2)\u003C/p>\u003Cp>\u003Cstrong>Schedule:\u003C/strong> 8:30 AM - 5:30 PM\u003C/p>\u003Cp>\u003Cstrong>Abstract:\u003C/strong> Recent research has increasingly focused on applying the Banach contraction principle in the broad area of systems and control. Similarly, this tool plays a key role in addressing timely problems in machine learning and dynamical neuroscience. Contracting dynamical systems inherently offer numerous safety and stability guarantees. Additionally, the theory of monotone operators in optimization theory serves as an important complement to these theoretical tools.\u003C/p>\u003Cp>The workshop will feature an extensive list of presentations by leading scientists from around the world on: \u003C/p>\u003Cul>\u003Cli>The foundations of contraction theory\u003C/li>\u003Cli>Theoretical developments for complex networks, including advances in synchronization and scalability\u003C/li>\u003Cli>Computational advances in the design of contraction metrics and contracting dynamical systems for solving optimization problems\u003C/li>\u003Cli>Applications to machine learning, planning, and robust control\u003C/li>\u003C/ul>\u003Cp>Of particular interest to the CDC audience will be findings on robust stability analysis and control design for both deterministic and stochastic systems, as well as formal robustness and stability guarantees for various learning-based control problems.\u003C/p>\u003Cp>This workshop will bring together experts from diverse backgrounds to discuss recent theoretical and computational advances, identify emerging challenges, and explore rapidly-developing application opportunities. It should appeal to both junior and senior researchers interested in systems, control, and learning. The control community's interest in these topics is evidenced by recent well-attended events, including a tutorial session at the 2021 IEEE CDC and a pre-conference workshop at the 2023 ACC.\u003C/p>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"http://motion.me.ucsb.edu/contraction-workshop-2024/\">\u003Cspan style=\"font-size:1.25rem;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003Cspan style=\"font-size:1.25rem;\">\u003Cstrong>: \u003C/strong>\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"http://motion.me.ucsb.edu/contraction-workshop-2024/\">\u003Cspan style=\"font-size:1.25rem;\">http://motion.me.ucsb.edu/contraction-workshop-2024/\u003C/span>\u003C/a>\u003Cbr> \u003C/p>","2024-07-19T17:44:20.526Z","2024-10-30T22:07:25.875Z","2024-07-19T17:47:24.959Z","84",[],"-51",{"id":116,"session":1431},{"id":116,"title":1432,"teaser":1433,"body":1434,"createdAt":1435,"updatedAt":1436,"publishedAt":1437,"url_path_id":1438,"contacts":1439,"url_path":1440},"Workshop 2: Control and Optimization in the Probability Space","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Liviu Aolaritei* (UC Berkeley), Giovanni Russo (University of Salerno), Florian Dörfler (ETH Zurich)\u003C/span>\u003C/p>","\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers \u003C/strong>(in alphabetical order)\u003Cstrong>:\u003C/strong> Liviu Aolaritei (UC Berkeley), Charlotte Bunne (EPFL), Yongxin Chen (Georgia Institute of Technology), Mario di Bernardo (University of Naples Federio II), Robert D. Mcallister (TU Delft), Maxim Raginski (University of Illinois at Urbana-Champaign), Giovanni Russo (University of Salerno), Bartolomeo Stellato (Princeton University), Bart Van Parys (CWI - the Netherlands), \u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location: \u003C/strong>Amber 2 (Floor 2)\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract\u003C/strong>: Driven by the recent advances and surge of interest in computational optimal transport and distributionally robust optimization within the machine learning and operations research communities, this workshop seeks to gather leading experts whose work lies at the crossroads of control theory and these emerging disciplines. This intersection of disciplines holds the promise to revolutionize the way we design high-performance control systems able to handle uncertainty in nonlinear, non-stationary and stochastic environments. The intersection between control, optimal transport and the distributionally robust paradigm indeed offers a fertile ground of new exciting theoretical challenges and modern real-world applications. \u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">In this context, this full-day workshop will enable the interaction between researchers in the areas of stochastic control, computational optimal transport, and distributionally robust optimization, with the aim of: (i) developing a deeper understanding of the fundamental ties between these related research topics; (ii) leveraging this understanding to design optimal control algorithms able to handle uncertainty in nonlinear, non-stationary and stochastic environments. In doing so, the workshop will focus around two research directions:\u003C/span>\u003C/p>\u003Cul>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cu>Control and Optimization in the face of distributional uncertainty. \u003C/u>Classical approaches in control and optimization assume that uncertainty can be modeled either in a robust (deterministic, norm-bounded) or a stochastic (one fixed distribution, e.g., Gaussian) fashion. This assumption constitutes a big limitation in modern data science applications, where often only a finite amount of samples from the uncertainty is available. In such situations, one is confronted with distributional uncertainty, whereby not only is the system affected by uncertainty, but also the underlying probability distribution of the uncertainty is unknown and only partially observable. This issue led to the development of a novel class of distributionally robust uncertainty models, termed ambiguity sets, which can be constructed in a principled fashion from partial statistical information about the uncertainty (e.g., samples). \u003Cstrong>This first research direction aims at addressing the new challenges\u003C/strong> introduced by ambiguity sets, namely the computational tractability, statistical soundness, and closed-loop guarantees of distributionally robust optimization and control problems. \u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cu>Dynamics and control in the space of densities\u003C/u>. Stochastic dynamical systems are naturally represented in the space of densities via the continuity equation or, more generally, via the Fokker-Planck equation. This viewpoint provides several benefits, presenting a macroscopic outlook on the system by focusing on the ensemble behavior rather than individual trajectories. As an example, in large multi-agent systems, like those modeling social networks or cellular dynamics, the density representation facilitates the description and analysis of the entire population's behavior, contrasting with the original state-space model which typically addresses only individual agents/cells. However, transitioning from the standard Euclidean space to the space of densities presents numerous challenges, ranging from fundamental issues like controllability and stability to practical computational considerations. \u003Cstrong>This second research direction will dive into these challenges\u003C/strong> through the lens of optimal transport, which has recently emerged as a powerful language to pose and address these problems.\u003C/span>\u003C/li>\u003C/ul>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Throughout the workshop, the methodological concepts will be motivated and illustrated by a myriad of exciting applications in machine learning, energy systems, network systems, and computational medicine. As apparent from the list of talks and the proposed schedule, the workshop has been built to be highly interactive and suitable for an audience with a diverse mix of academic/industrial backgrounds. Ultimately, our aim is indeed to create a vibrant space that appeals to both academic scholars and industry professionals, fostering a rich exchange of theoretical insights and practical applications. \u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule\u003C/strong>: 9:00 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">The schedule for this full-day event is organized around 4 interlinked tracks (see below). The workshop will consist of talks of 25 minutes plus 5 minutes for Q&A after each individual talk. Besides this, we also built in the schedule breakout sessions to  promote interactions. These breakout sessions will be a space for students to give spotlight presentations (3-5 minutes) where they could showcase their late breaking results (\u003Cu>if you are a student interested in giving a spotlight presentation please contact one of the organizers\u003C/u>).\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>Time\u003C/td>\u003Ctd>Event\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cstrong>Track 1- Distributionally Robust Control\u003C/strong>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">09.00 - 09.10\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Opening Remarks\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">09.10 - 09.40\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Capture, Propagate, and Control Distributional Uncertainty (\u003Ci>L. Aolaritei\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">09.45 - 10.15\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Closed-loop guarantees for distributionally robust model predictive control (\u003Ci>R. Mcallister\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">10.15 - 10.30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Breakout Session 1\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>10.30 -11.00\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>COFFEE BREAK\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Track 2 - Distributionally Robust Optimization\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11.00 - 11.30\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Disciplined Decisions in the Face of Uncertainty and Data (\u003Ci>B. Van Parys\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11.35 - 12.05\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Learning Decision-Focused Uncertainty Sets for Robust Optimization (\u003Ci>B. Stellato\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">12.05 - 12.20\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Breakout Session 2\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">12.20 - 13.50\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>LUNCH BREAK\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Track 3 - Control in the Space of Densities\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">13.50 - 14.20\u003C/span>\u003C/td>\u003Ctd>\u003Ci>\u003Cspan lang=\"en-US\" dir=\"ltr\">Control and estimation of multi-agent systems via unbalanced multi-marginal optimal transport (J. Karlsson)\u003C/span>\u003C/i>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>14.25 - 14.55\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Optimal control of the Liouville equation (\u003Ci>M. Raginsky\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>15.00 - 15.30\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Forward and Inverse Problems with Entropy Regularization (\u003Ci>G. Russo\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>15.30 - 16.00\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>COFFEE BREAK\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Track 4 - Dynamics in the Space of Densities\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16.00 - 16.30\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Controlling large-scale multiagent systems: a continuification-based approach (\u003Ci>M. di Bernardo\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16.35 - 17.05\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Predicting Patient Treatment Outcomes using Diffusion Models and Optimal Transport (\u003Ci>C. Bunne\u003C/i>)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>17.10 - 17.30\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Breakout Session 3\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website:\u003C/strong> \u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/unisa.it/cdc-2024-workshop/home-page\">\u003Cspan style=\"background-color:transparent;color:#000000;\">https://sites.google.com/unisa.it/cdc-2024-workshop/home-page\u003C/span>\u003C/a>\u003C/p>","2024-07-19T17:49:55.427Z","2024-10-30T22:07:42.021Z","2024-07-19T17:49:58.039Z","89",[],"-56",{"id":343,"session":1442},{"id":343,"title":1443,"teaser":1444,"body":1445,"createdAt":1446,"updatedAt":1447,"publishedAt":1448,"url_path_id":1449,"contacts":1450,"url_path":1451},"Workshop 4: Safe and Secure Learning-Enabled Systems ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Thinh T. Doan* (University of Texas at Austin), Kyriakos G. Vamvoudakis (Georgia Tech)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 1 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract: \u003C/strong> Harnessing the power of machine learning to continuously monitor and detect anomalies advances the state of the art in instrumentation control. Learning-enabled systems have been rapidly increasing in size and acquiring new capabilities. These systems are typically deployed in complex  operating environments, so their safety becomes extremely important. Ensuring safety requires that systems are robust to extreme events while we can monitor them for anomalous and unsafe behavior. While traditional machine learning systems are evaluated pointwise with respect to a fixed test set, such static coverage provides only limited assurance when exposed to unprecedented conditions in complex operating environments. One key question that remains unanswered is “how can we design and deploy learning-enabled systems that can be robust to extreme events while monitoring them for anomalous and unsafe behavior?” Indeed, given the increasing deployment of learning-enabled systems in various critical applications, guaranteeing security and safety of these systems has been an active research topic in different communities (e.g., control and machine learning) and has received a great interest from many funding agencies (e.g., NSF through the recent Safe Learning-Enabled Systems program). \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The objective of this workshop is to bring leading researchers (including 2 NAE members and 3 female professors) in safe and secure learning-based control and verification, to discuss the latest developments, future directions, and explore possible novel directions in the intersection of learning, optimization, and game theory areas. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop will feature one plenary talk (1 hour) and 9 half an hour talks. The workshop will conclude with a panel discussion on future research topics for safety and security of learning enabled systems. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers (order they appear in the schedule):\u003C/strong> Alberto L. Sangiovanni-Vincentelli (UC Berkeley), John Baras (University of Maryland, College Park), Naira Hovakimyan (UIUC), George Pappas (U Pen), Thomas Parisini (Imperial), Alessandro Astolfi (Imperial), Kyriakos G. Vamvoudakis (GaTech), Melanie Zeilinger (ETH), Majid Zamani (CU Boulder), Necmiye Ozay (U. Mich)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">We believe that with this line of diverse speakers our workshop not only will provide fruitful discussions on multiple angles of security and safety for learning-enabled systems but also will encourage the high attendance of various researchers/students from different groups, especially female participants.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 9:00 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>Time\u003C/td>\u003Ctd>Speaker\u003C/td>\u003Ctd>Title\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>9:00 - 10:00\u003C/td>\u003Ctd>Alberto L. Sangiovanni-Vincentelli\u003C/td>\u003Ctd>Plenary talk - TBD\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>10:00 - 10:30\u003C/td>\u003Ctd>John Baras\u003C/td>\u003Ctd>Learning in Trustworthy Autonomy: Safety and Security via Risk-sensitive Planning\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>10:30 - 11:00\u003C/td>\u003Ctd>Coffee Break\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:00 - 11:30\u003C/td>\u003Ctd>Naira Hovakimyan\u003C/td>\u003Ctd>Safe learning in Autonomous Systems\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:30 - 12:00\u003C/td>\u003Ctd>George Pappas\u003C/td>\u003Ctd>TBD\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>12:00 - 13:30\u003C/td>\u003Ctd>Lunch Break\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>13:30 - 14:00\u003C/td>\u003Ctd>Thomas Parisini\u003C/td>\u003Ctd>Learning from Data Nonlinear Systems Models with Guaranteed Stability Properties\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>14:00 - 14:30\u003C/td>\u003Ctd>Alessandro Astolfi\u003C/td>\u003Ctd>Resilient Distributed optimization and adaptation via active interconnections\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>14:30 - 15:00\u003C/td>\u003Ctd>Kyriakos G. Vamvoudakis\u003C/td>\u003Ctd>Adversarially Robust and Safe Learning \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>15:00 - 15:30\u003C/td>\u003Ctd>Melanie Zeilinger\u003C/td>\u003Ctd>TBD\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>15:30 - 16:00\u003C/td>\u003Ctd>Mazid Zamani\u003C/td>\u003Ctd>A Correct-by-Construction Paradigm for Designing Autonomous Systems\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16:00 - 16:30\u003C/td>\u003Ctd>Necmiye Ozay\u003C/td>\u003Ctd>Learning control specifications from multi-modal data\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16:30 - 17:30\u003C/td>\u003Ctd>Panelists\u003C/td>\u003Ctd>Panel Discussion\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Website: \u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/ssles-workshop-cdc-2024\">\u003Cspan style=\"background-color:transparent;color:#1155cc;\">\u003Cu>https://sites.google.com/view/ssles-workshop-cdc-2024\u003C/u>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T03:56:37.988Z","2024-10-30T22:08:51.055Z","2024-07-20T03:57:11.452Z","94",[],"-61",{"id":354,"session":1453},{"id":354,"title":1454,"teaser":1455,"body":1456,"createdAt":1457,"updatedAt":1458,"publishedAt":1459,"url_path_id":1460,"contacts":1461,"url_path":1462},"Workshop 5: Control Architecture Theory (CAT) ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Aaron D. Ames (California Institute of Technology), Nikolai Matni (University of Pennsylvania), Gioele Zardini* (MIT)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Amber 4 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract: \u003C/strong>The design and control of complex systems stands out as one of the paramount challenges of this century.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Such systems are labeled as complex not only due to the intricacies of their individual components, but also because their functioning hinges on complex \u003Ci>interactions\u003C/i> among these components, across domains and scales.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">To give a sense of the kind of systems we are interested in, think about the complex circuit governing a sensor employed in autonomous driving context, and autonomous vehicle which leverages the sensor, as well as a number of other complex hardware and software components within the autonomy stack, a fleet of autonomous vehicles of this kind, deployed and controlled following certain objectives, and interacting via a complex patterns, and a mobility system leveraging Autonomous Mobility-on-Demand (i.e., the fleet) systems as well as standard transit options.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Each of these subsystems is complex to design and control per se, and is influenced and influences other ones at different scales.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">In this workshop we are driven by the need for a robust theory concerning layered control architectures (LCAs) across various complex systems, ranging from power systems and communication networks to autonomous robotics, bacteria, and human sensorimotor control.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Such systems exhibit exceptional capabilities, yet lack a cohesive, compositional theory for analysis and design, primarily due to their diverse domains. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Conversely, there exists a fundamental set of control concepts and theories which are universally applicable and can accommodate domain-specific adaptations.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">In this context, however, control methods are often limited to work for individual components of larger systems, lacking comprehensive theoretical foundations.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Although fragments of a control architecture theory have emerged across disparate disciplines and domains, a unified theory and community are lacking. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Against this backdrop, the objective of this workshop, organized as a companion to an invited session on the same subject, is to cultivate a new interdisciplinary community which considers control architectures and systems theory as a central focus of study.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">In particular, we will bring together experts from a wide range of disciplines, spanning robotics, control, applied mathematics, systems biology, aerospace, etc., with the goal of establishing a common language and core set of challenge problems and techniques.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">A key outcome of the workshop will be a white paper laying out a research program in this area.\u003C/span>\u003C/p>\u003Cp>\u003Cbr>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:45 AM - 5:30 PM, and speakers/panelists include Aaron Ames (Caltech), Domitilla Del Vecchio (MIT), John Doyle (Caltech), Florian Dörfler (ETHZ), Nadia Figueroa (UPenn), Nikolai Matni (UPenn), Lisa Li (Michigan), Manfred Morari (UPenn), Alberto Sangiovanni-Vincentelli (UC Berkeley), Alberto Speranzon (Lockheed Martin), Paulo Tabuada (UCLA), and Gioele Zardini (MIT).\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The correct order of the talks (30 minutes each) is being determined, and will appear on the webpage. The workshop will end with a panel discussion.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website:\u003C/strong> \u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://cat-cdc24.github.io/\">\u003Cspan style=\"background-color:transparent;color:#1155cc;\">\u003Cu>https://cat-cdc24.github.io/\u003C/u>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T03:58:41.415Z","2024-11-04T03:14:16.263Z","2024-07-20T03:58:43.909Z","95",[],"-62",{"id":396,"session":1464},{"id":396,"title":1465,"teaser":1466,"body":1467,"createdAt":1468,"updatedAt":1469,"publishedAt":1470,"url_path_id":1471,"contacts":1472,"url_path":1473},"Workshop 6: Leveraging bifurcations for control of intelligent and collective behaviors ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Anastasia Bizyaeva* (University of Washington), Alessio Franci (University of Liege)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers: \u003C/strong>Naomi Ehrich Leonard (Princeton University), Rodolphe Sepulchre (KU Leuven and Cambridge University), Fernando Castaños (Cinestav-IPN), Andreagiovanni Reina (University of Konstanz and Max Planck Institute of Animal Behavior), Juncal Arbelaiz (Princeton University), Haimin Hu (Princeton University), Charlotte Cathcart (Princeton University), Shinkyu Park (King Abdullah University of Science and Technology), Thiago Burghi (Cambridge University), Guillaume Drion (University of Liege), Nak-seung Patrick Hyun (Purdue University)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 6 (Mezzanine/Intermediate floor)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> From single-celled organisms to animal groups and human societies, living beings across scales sense their environment and react to it adaptively for survival. In doing so, they provide compelling examples of control systems capable of generating extremely robust and yet adaptable intelligent behaviors. Growing evidence has pointed to nonlinearity and, in particular, to bifurcations in nonlinear models as key ingredients for \u003Ci>understanding \u003C/i> the robust adaptability of these systems. To engineer autonomous systems that provably inherit the robust adaptability of their biological counterparts, control engineers must leverage these scientific insights and embrace bifurcation as a \u003Ci>design principle\u003C/i>. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Bifurcations have a constructive role in natural and societal intelligence. A local bifurcation point is a parameter regime at which a solution of a nonlinear system changes stability. This is a point of ultra-sensitivity at which a control system can rapidly change its behavior in response to changes in the environment, even when those changes are arbitrarily small. This ultra-sensitivity can be observed in human decision-making, for example when a sudden event that requires a change in behavior happens while riding a bike or cooking a meal. Collective behaviors also exhibit ultra-sensitive responses, e.g., as a bacterial society does when antibiotics are poured into its environment, or as a human society can choose to do when imminent dangers are around the corner. Away from the ultra-sensitive bifurcation point, a control system ruled by bifurcations is organized into distinctively different robust behaviors associated with choosing a control action or strategy over alternative ones: steering the bike left instead of right into a pedestrian; turning the stove off instead of burning the sauce; developing a biofilm instead of remaining exposed to antibiotics; transitioning into a more sustainable life style instead of doing business as usual. The co-existence of many different possible control choices is captured by the rich multi-stable attractor landscape that emerges at bifurcations. By navigating this landscape in response to inputs or in pursuit of goals, an agent can continuously adapt its behavior in a robust yet sensitive fashion. In other words, \u003Ci>bifurcations can be leveraged for control\u003C/i> to achieve robust and adaptive behaviors in ever-changing and unpredictable environments. This is diametrically \u003Ci>opposed to\u003C/i> the classical approach of  \u003Ci>controlled bifurcations\u003C/i> for stabilization problems, in which a typical objective is to steer a system away from a bifurcation point, ideally achieving global stability.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">To understand natural and societal collective and intelligent behaviors, and to draw inspiration from them for the design, analysis, and control of more robust and adaptable artificial intelligent and collective behaviors, a new synthesis of bifurcation and systems theories is needed. This workshop aims at providing the state-of-the art of recent efforts toward this new synthesis, and to explore new ideas toward its realization in applications.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule: \u003C/strong>9:00 AM - 5:45 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>09:00 - 09:15\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Workshop introduction & opening remarks\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>09:15 - 10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Naomi Ehrich Leonard\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Bifurcation theory for versatile and agile control\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:00 - 10:30 \u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:30 - 11:15\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Rodolphe Sepulchre\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">The thresholds of an excitable system\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:15 - 12:00 \u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Fernando Castaños\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Analysis and design of bifurcations: non-smooth settings\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>12:00 - 13:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>13:00 - 13:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Shinkyu Park\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Opinion-driven decision making for spatial navigation\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>13:30 - 14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Charlotte Cathcart\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Excitable decision-making for agile control\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:00 - 14:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Andreagiovanni Reina\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Inhibitory signals enable robust collective decision-making in robot swarms\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:30 - 15:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Nak-seung Patrick Hyun\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Bifurcation in latch-mediated spring actuation systems (LaMSA) across biology and robotics\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:00 - 15:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:30 - 16:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Juncal Arbelaiz\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>Excitable crawling\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:00 - 16:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Guillaume Drion\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Using bifurcations for the analysis and design of recurrent neural network dynamics\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:30 - 17:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Thiago Burghi\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Predicting bifurcations in biological neural circuits\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:00 - 17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Haimin Hu\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Learning neural opinion dynamics for split-second game-theoretic interactions\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:30 - 17:45 \u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Workshop wrap-up & closing remarks\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Cbr>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website:  \u003C/strong>\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/cdc2024-bifurcations-workshop\">\u003Cspan style=\"background-color:transparent;color:#000000;\">https://sites.google.com/view/cdc2024-bifurcations-workshop\u003C/span>\u003C/a>\u003C/p>","2024-07-20T03:59:48.392Z","2024-11-11T21:09:26.940Z","2024-07-20T03:59:50.468Z","96",[],"-63",{"id":406,"session":1475},{"id":406,"title":1476,"teaser":1477,"body":1478,"createdAt":1479,"updatedAt":1480,"publishedAt":1481,"url_path_id":1482,"contacts":1483,"url_path":1484},"Workshop 7: Control of Multiagent Systems: Challenges and Solutions ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers\u003C/strong>: Tansel Yucelen* (University of South Florida), Deniz Kurtoglu (University of South Florida), David W. Casbeer (Air Force Research Laboratory), Dejan Milutinovic (University of California at Santa Cruz)\u003C/span>\u003C/p>","\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>\u003Cu>Speakers (Alphabetical)\u003C/u>\u003C/strong>: David Casbeer (Air Force Research Laboratory), Venanzio Cichella (University of Iowa), Magnus Egerstedt (University of California at Irvine), Rafael Fierro (University of New Mexico), Deniz Kurtoglu (University of South Florida), Dejan Milutinović (University of California at Santa Cruz), Kevin Moore (Colorado School of Mines), Maria Prandini (Politecnico di Milano), Rifat Sipahi (Northeastern University), Yan Wan (University of Texas at Arlington), Tansel Yucelen (University of South Florida)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>\u003Cu>Location\u003C/u>\u003C/strong>: Amber 5 (Floor 2)\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>\u003Cu>Abstract\u003C/u>\u003C/strong>: Over the last two decades, technology has significantly advanced the development of integrated systems that combine mobility, computing, and communication on a single platform. As a result, we have rapidly entered a new era in which teams of agents, known as multiagent systems, interact with each other to influence their motions for cooperatively performing a wide array of civilian and military applications. These applications range from surveillance and reconnaissance to unmanned system operations and energy management. It is therefore not surprising that the overall robotics market value has seen a dramatic increase with the expectation to reach around 200 billion U.S. dollars by 2025. This has led to a significant research activity focused on how to control these robot teams through local interactions (i.e., distributed control) to achieve necessary cooperative behaviors.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Specifically, distributed control approaches can typically be classified into two categories; namely, “leaderless distributed control approaches,” where all agents perform a task without an external command, and “leader-follower distributed control approaches,” where a subset of agents (referred to as leaders) receive external commands that influence the behavior of other agents (referred to as followers) in the multiagent system. The \u003Cstrong>objective\u003C/strong> of this workshop is to cover the state-of-the-art advancements in the field of multiagent systems with a focus on leaderless and leader-follower distributed control approaches. Participants will have the opportunity to learn about the challenges and solutions on problems related to \u003Cstrong>a) \u003C/strong>spatiotemporal, communication, and nonholonomic \u003Cstrong>constraints\u003C/strong>; \u003Cstrong>b)\u003C/strong> multiagent system \u003Cstrong>resilience\u003C/strong> against uncertainties and time-delays; and \u003Cstrong>c)\u003C/strong> \u003Cstrong>autonomy\u003C/strong> including coordination, collaboration, optimization, and decision-making with \u003Cstrong>applications\u003C/strong> to mobile ground, aerial, and space robots as well as energy systems.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Constraints. \u003C/strong>Spatiotemporal constraints refer to the limitations on the movement and actions of agents that are imposed by both space and time. These constraints can include factors such as physical boundaries and timing requirements for coordinated tasks. Furthermore, communication constraints refer to the limitations on the exchange of information between agents, where these constraints can arise due to limited communication range, bandwidth, or signal interference. Nonholonomic constraints are also restrictions on the motion of agents, where the direction of motion is limited by the steering mechanism. Addressing all these constraints is crucial for effectively using multiagent systems in real-world applications. \u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Resilience. \u003C/strong>Achieving resilience in real-world applications is also highly important for the safe operation of multiagent systems. In this context, uncertainties and time-delays play a crucial role in threatening safety as they can lead to unpredictable behavior and delayed responses. In particular,  uncertainties can arise from a broad spectrum of sources including unpredictable environmental conditions and modeling inaccuracies, while time-delays can occur in agent-to-agent communication and control loops. Ensuring resilience against these factors is key to maintaining multiagent system stability and predictable performance.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Autonomy.\u003C/strong> Autonomy requires coordination, collaboration, optimization, and decision- making with no or minimal human intervention. Specifically, coordination and collaboration are central to the autonomous operation of multiagent systems. Typically, the strategy involves dividing team-level tasks into manageable subtasks with each agent responsible for executing its assigned portion in a coordinated manner. Yet, by integrating agents with diverse capabilities, the potential arises to unlock entirely new functionalities and skills. Moreover, optimization for autonomous motion planning and resource allocation is at the heart of effective decision- making. By properly formulating and solving optimization problems, agents have the ability to determine the most efficient ways for achieving their objectives while adhering to constraints and considering the actions of other agents. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Covering the topics on constraints, resilience, and autonomy is crucial for the advancement and success of the next-generation of multiagent systems, where we organize this workshop on these key topics. As given in the schedule below, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 1\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> is related to spatiotemporal constraints, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talks 2\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> and \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>3 \u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">are related to communication constraints, and \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 3\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> is also related to nonholonomic constraints (i.e., these talks are related to theme \u003Cstrong>a)\u003C/strong> of this workshop). In addition, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talks 4 \u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">and \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>5\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> are related to multiagent system resilience against uncertainties and time-delays (i.e., these talks are related to theme \u003Cstrong>b)\u003C/strong> of this workshop). Furthermore, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 6\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> is related to coordination and collaboration, whereas \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talks 7\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">-\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>11 \u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">are related to optimization and decision-making aspects in autonomy (i.e., these talks are related to theme \u003Cstrong>c)\u003C/strong> of this workshop). Finally, it is important to note that \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talks 1\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>2\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>6\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">-\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>11\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> will further touch upon multiagent system \u003Cstrong>applications\u003C/strong> to mobile ground, aerial, and space robots as well as energy systems.\u003C/span>\u003C/p>\u003Cp> \u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>08:30 - 09:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Tansel Yucelen \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 1\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Distributed Control under Spatiotemporal Constraints\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>09:00 - 9:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Venanzio Cichella \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 2\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Coordination and Motion Planning Strategies for Multi-Vehicle Systems in Communication-Constrained Environments\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:30 - 10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Deniz Kurtoglu \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 3\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Norm-Free Event-Triggered Distributed Control and Performance Recovery for Nonholonomic Multiagent Systems\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>10:00 - 10:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Coffee Break\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:30 - 11:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Magnus Egerstedt \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 4\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>From Coordination to Collaboration in Heterogeneous Multi-Robot Systems\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:00 - 11:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Kevin Moore \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 5\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>A Dynamic Network Perspective on Resilient Control\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:30 - 12:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Rifat Sipahi \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 6\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Delay-Based Controllers and Unintentional Delays in Multi-Agent Network Control\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>12:00 - 13:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Lunch\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>13:30 - 14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Rafael Fierro \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 7\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Multiagent Coordination for On-Orbit Servicing and Satellite Operation Extension\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:00 - 14:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>David Casbeer \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 8\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Cooperative Tactical Defense\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:30 - 15:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Dejan Milutinović \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 9\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Robust Decision Making for Autonomy\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:00 - 15:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Yan Wan \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 10\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>UAV Traffic Management: Autonomy and Airspace Capacity\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>15:30 - 16:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Coffee Break\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:00 - 16:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Maria Prandini \u003C/strong>(\u003C/span>\u003Cspan style=\"background-color:transparent;color:#6aa84f;\">\u003Cstrong>Talk 11\u003C/strong>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Optimization and Management of Multiple Energy Resources for Balancing Services Provision\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:30 - 17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Panel Discussion\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"http://tinyurl.com/cdc2024-workshop/\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:00:58.922Z","2024-10-30T22:10:29.209Z","2024-07-20T04:01:02.107Z","97",[],"-64",{"id":1181,"session":1486},{"id":1181,"title":1487,"teaser":1488,"body":1489,"createdAt":1490,"updatedAt":1491,"publishedAt":1492,"url_path_id":1493,"contacts":1494,"url_path":1495},"Workshop 8: Fair Decision-Making and Societally-Aware Control in Networked Systems ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Valentina Breschi* (Eindhoven University of Technology), Eugenia Villa (Politecnico di Milano), Chiara Ravazzi (National Research Council of Italy), Fabrizio Dabbene (National Research Council of Italy), Mara Tanelli (Politecnico di Milano), Marco Pavone (Stanford University)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Valentina Breschi* (Eindhoven University of Technology), Eugenia Villa (Politecnico di Milano), Chiara Ravazzi (National Research Council of Italy), Fabrizio Dabbene (National Research Council of Italy), Mara Tanelli (Politecnico di Milano), Marco Pavone (Stanford University)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 5 (Mezzanine/Intermediate floor)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers: \u003C/strong>Alessandro Fabris (Max Planck Institute for Security and Privacy (MPI-SP) Bochum, Germany), Eugenia Villa (Politecnico di Milano), Andreas A. Malikopoulos (Cornell University, USA), Carlos Canudas-de-Wit (CNRS, GIPSA-lab, France), Karl Johansson and Zifan Wang (KTH Royal Institute of Technology, Sweden), Giulia De Paquale (ETH Zürich, Switzerland), Naomi Leonard (Princeton University, USA), Ali Jadbabaie (MIT, USA), Mengbin Ye (Curtin University, Australia).\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract: \u003C/strong>This workshop aims to bring together researchers and scientists to discuss topics related to the theory of control of networked systems, addressing pressing societal challenges such as promoting fairness in control strategies and accounting for the impact of feedback and social engagement in interaction-based decision-making. The workshop is designed with a strong interdisciplinary component, and the talks, organized in four separate sessions, include relevant topics that combine classical control techniques with game theory and opinion dynamics modeling, emphasizing the practical application of theoretical frameworks to real problems. A round table at the conclusion of the day will offer significant insights into the latest developments in the field, open research directions, and potential applications in mobility, economics, and recommendation systems.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:30 AM - 4:45 PM\u003C/span>\u003C/p>\u003Cp>\u003Cbr> \u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>8:30 - 8:40 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Introduction & Motivation\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Fabrizio Dabbene and Mara Tanelli\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cu>Session 1: How can fairness be considered in decision-making?\u003C/u>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>8:45 - 9:15 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Estimated fairness from limited data\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Alessandro Fabris\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:20-9:50 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Empowering Fairness: A holistic control-oriented framework for diversity-aware innovation diffusion\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Eugenia Villa\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cu>Session 2: Can mobility models be socially aware and fair?\u003C/u>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:55 - 10:35 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Fair decision-making for socially optimal emerging mobility systems\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Andreas A. Malikopoulos\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:40 - 10:55 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Coffee break\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> \u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:55 - 11:25 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">EVs and renewable energy: paving the way for greener electromobility networks\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Carlos Canudas-de-Wit\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cu>Session 3: The power of feedback in decision-making at a societal scale\u003C/u>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:30 - 12:00 AM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">How does feedback information influence risk-averse games?\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Karl Johansson & Zifan Wang\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>12:00 AM - 1:00 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Lunch break\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>1:30 - 2:00 PM\u003C/strong> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">A quantitative exploration of users-recommender systems interaction over online platforms via online feedback optimization\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Giulia De Pasquale\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cu>Session 4: How can opinion formation be modeled?\u003C/u>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>2:05 - 2:35 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Nonlinear opinion dynamics for the study of fair decision-making and societally-aware control in networked systems\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Naomi E. Leonard\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>2:40 - 3:10 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Tracking truth with liquid democracy\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Ali Jadbabaie\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>3:10 - 3:25 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Coffee break\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\"> \u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>3:25 - 3:55 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Development of psychologically-informed models of social dynamics using experimental data\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Mengbin Ye \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>4:00 - 4:30 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Panel discussion. Moderator: Marco Pavone, Panelists: Karl Johansson, \u003C/span>\u003Cspan style=\"background-color:transparent;color:#212121;\">Ali Jadbabaie, Mara Tanelli, Andreas A. Malikopoulos\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>4:30 - 4:45 PM\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Discussion and concluding remarks\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Fabrizio Dabbene\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Cbr>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/cdc-2024-fairworkshop/home\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:02:22.348Z","2024-12-11T11:20:02.368Z","2024-07-20T04:02:24.260Z","98",[],"-65",{"id":1228,"session":1497},{"id":1228,"title":1498,"teaser":1499,"body":1500,"createdAt":1501,"updatedAt":1502,"publishedAt":1503,"url_path_id":1504,"contacts":1505,"url_path":1506},"Workshop 9: Large Population Teams: Control, Equilibria, and Learning ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Aditya Mahajan (McGill University), Panagiotis Tsiotras* (Georgia Institute of Technology), Serdar Yüksel (Queen’s University)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Speakers (Alphabetically):\u003C/strong> Tamer Basar (UIUC),  Karthik Elamvazhuthi (University of California Riverside), Mathieu Lauriere (New York University, Shangai),  Aditya Mahajan (McGill University),  Nuno Martins (University of Maryland), Lacra Pavel (University of Toronto),  Vijay Subramanian (University of Michigan), Panagiotis Tsiotras (Georgia Institute of Technology), Serdar Yüksel (Queen’s University)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 8 (Mezzanine/Intermediate floor)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> Stochastic teams entail a collection of decision makers / players /agents acting together to optimize a common cost function, but not necessarily having access to the same information.  It is by now known that such problems are challenging owing to information structure-dependent subtleties even in the team setup. In the game setup, informational dependence makes solutions very fragile in that even solution concepts need to be refined, the value of information can be negative (unlike in collaborative teams), the value of information is not necessarily continuous, and the presence or absence of common randomness turns out to be a key attribute. Large-population games become even more challenging when one or more competing teams are involved. There are two major challenges when trying to solve such competitive team problems: First, large-population team problems are computationally challenging since the solution complexity increases exponentially with the number of agents, and, in general, the team optimal control problems belong to the NEXP complexity class. Second, competitive team problems are conceptually challenging due to the elusive nature of the opponent team, and thus one cannot directly deploy approximation techniques available in the large-population game literature. Despite the great advances in mean-field approximations for multi-agent systems for specific classes of single team games, several unresolved challenges still exist for the more realistic case of competitive team problems.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The proposed workshop intends to address the above needs and by bringing ogether researchers from various disciplines (different areas of engineering, mathematics, and data science) working on the theory and applications of decentralized systems with large number of units or agents under a variety of system and evolution dynamics, information structures, performance criteria, and application areas. A common thread will be to understand the optimality and equilibrium behaviour, scaling behaviour with the number of agents, and learning dynamics; all in both the associated mathematical theory as well as in the context of emerging engineering and applied science applications. Due to the interdisciplinary nature of such problems involving optimal control, stochastic control, game theory, multi-agent systems, and robotics, we intend to establish connections between various formulations adopted in the community and bring researchers who have been using alternative setups, solutions approaches, and applications to allow for exchange of ideas and formulation of new research directions and collaborations. One other main goal of this workshop is to inspire a future generation of researchers in this vibrant field.\u003C/span>\u003C/p>\u003Cp> \u003C/p>\u003Cfigure class=\"table\" style=\"float:left;\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">8:30am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Opening Remarks\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">8:40am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Invited Session 1\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">8:40-9:20am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Large Population Games with Hybrid Modes of Behavior\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Tamer Basar (UIUC) \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">9:20-10:00am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Mean-Field Stabilization of Control-Affine Systems to Probability Densities\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Karthik Elamvazhuthi (LANL) \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">10:00-10:40am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Deep Reinforcement Learning for Mean-field Type Games\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Mathieu Lauriere (NYU Shanghai)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">10:40-11:00am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Break\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">11:00am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Invited Session 2\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">11:00-11:40am\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Mean-Field Games Among Teams\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Aditya Mahajan (McGill) \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">11:40-12:20pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Incentive Design and Learning in Large Populations: A System- Theoretic Approach With Applications To Epidemic Mitigation\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Nuno Martins (UMD)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">12:20 -1:50pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch & Poster Session\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">1:50pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Invited Session 3\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">1:50-2:30pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Higher-order Learning in Multi-Agent Games\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lacra Pavel (U Toronto)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">2:30-3:10pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Dynamic Games Among Teams with Delayed Intra-Team Information Sharing\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Vijay Subramanian (UMich)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">3:10-3:30pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Break\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">13:30pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Invited Session 4\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">3:30-4:10pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Zero-Sum Games Between Large-Population Teams under Mean-Field Sharing\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Panagiotis Tsiotras (Georgia Tech) \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">4:10-4:50pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Equivalence between Controlling a Large Population and a Representative Agent: Optimality, Learning, and Games (among Teams)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Serdar Yüksel (Queen's University)\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">4:50-5:30pm\u003C/span>\u003C/td>\u003Ctd style=\"background-color:#ffffff;padding:4pt;vertical-align:top;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Poster Session & Open Discussion\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp> \u003C/p>\u003Cp> \u003C/p>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://dcslgatech.github.io/cdc24-large-teams-workshop/\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:09:11.113Z","2024-11-18T12:30:57.187Z","2024-07-20T04:09:15.524Z","99",[],"-66",{"id":1273,"session":1508},{"id":1273,"title":1509,"teaser":1510,"body":1511,"createdAt":1512,"updatedAt":1513,"publishedAt":1514,"url_path_id":1515,"contacts":1516,"url_path":1517},"Workshop 10: Complex Socio-Technical Networked Dynamics ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Angela Fontan (KTH Royal Institute of Technology), Karl H. Johansson (KTH Royal Institute of Technology), Pedro U. Lima (Universidade de Lisboa), Sergio Pequito (Universidade de Lisboa), Alessandro Rizzo (Politecnico di Torino), Lorenzo Zino* (Politecnico di Torino)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 3 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract: \u003C/strong>Complex socio-technical systems are increasingly becoming a cornerstone of our societies, playing a key role in shaping numerous facets of our daily life, from production and communication, to robotics and information accessibility. A key feature of such systems in the presence of intertwined layers involving technology, human behavior, and infrastructure networks. The pervasive presence and impact of these systems in our societies calls for a deeper understanding of such complexity towards the development of a unified platform to explore the multifaceted dimensions of socio-technical systems.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Motivated by such a key challenge, we propose a workshop with the primary objective of creating a platform for researchers to discuss innovative ideas in the realm of complex socio-technical systems. To this aim, we selected a list of speakers from research units specialized in diverse aspects of modeling, analysis, and control of complex socio-technical systems, with a broad spectrum of expertise spanning from the development and analysis of mathematical models and control protocols for cyber-physical-human-systems, complex social networks, and the exploration of human-robot interactions. The list of speakers will be complemented by a conclusive session in which junior researchers (PhD students and postdocs, which will be selected via an open call) will have the opportunity to illustrate and discuss their innovative approaches to complex socio-technical networked systems.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">This workshop will offer a diverse yet consistent and thorough overview of the ongoing efforts towards hacking complex socio-technical systems, showcasing how systems- and control-theoretic approaches offer powerful tools to understand, model, and control such dynamics, while bringing innovation from other fields, such as evolutionary game theory, network science, experimental psychology, and robotics.\u003C/span>\u003C/p>\u003Cp> \u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>09:15 - 10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Mario di Bernardo\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Coordination, synchronization, and control in complex human networks\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:00 - 10:25\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Francesca Parise\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Large-scale multi-agent systems: Achieving tractability via graph limits\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>10:25 - 10:55\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Coffee break\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:55 – 11:40\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Ming Cao\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Stochastic games and learning in populations\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:40 - 12:05\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Emma Tegling\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Polarization and agreement in networks of biased and stubborn agents\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>12:05 - 12:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Bruno Lacerda\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Estimating human performance in shared autonomy systems through interaction\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>12:30 - 14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Lunch break\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:00 - 14:25\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Philip E. Paré\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"color:rgb(0,0,0);\">A framework for counterfactual analysis, strategy evaluation, and control of epidemics using reproduction number estimates\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:25 - 14:50\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Angela Fontan\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Collective decision-making in smart homes\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:50 - 15:15\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Nicanor Quijano\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Exploring sustainable cities: Model approaches and application of population games\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>15:15 - 15:30\u003C/strong> \u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Coffee break\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:30 - 15:55\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Sérgio Pequito\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Fractional cyber-neural systems\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:55 - 16:20\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Lorenzo Zino\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Adaptive-gain control for evolutionary game-theoretic dynamics\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:20 - 17:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Junior Researcher Session\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:00 - 17:30 \u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Panel Discussion and closing remarks\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/socio-technical-cdc2024\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:10:15.731Z","2024-12-09T14:15:34.923Z","2024-07-20T04:10:31.390Z","100",[],"-67",{"id":602,"session":1519},{"id":602,"title":1520,"teaser":1521,"body":1522,"createdAt":1523,"updatedAt":1524,"publishedAt":1525,"url_path_id":1526,"contacts":1527,"url_path":1528},"Workshop 11: Past and Future in Control of Networked Systems: Insights and Perspectives ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Jeff S. Shamma (University of Illinois Urbana-Champaign), Giacomo Como (Politecnico di Torino), Luca Schenato (University of Padova), Lacra Pavel* (University of Toronto)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 4 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract: \u003C/strong>The objective of this workshop is to provide insight and perspectives on the area of control of networked systems. The workshop coincides with the 10-year anniversary of the IEEE Transactions on Control of Networked Systems. Over the past fifteen years or so important strides have been made in research on decision and control systems characterized by a distributed or networked architecture, be it in modeling, analysis, estimation, design, or implementation. New research avenues have been opened and established:  from collaborative control, distributed learning, multi-agent systems, distributed optimization, control of collective behavior, distributed estimation, game theory, dynamical systems over graphs, coevolutionary networks, synchronization, large-scale complex systems, to control with communication constraints. Application areas relevant to control of network systems include smart infrastructure, multi-robot systems and swarm robotics, systems biology, neuroscience, smart health, computing, communications, transportation, manufacturing, power systems, cyber-physical and social systems, sensor networks, and social networks.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop aims to provide the framework for an introspective about the past and future of network control. Featuring invited talks from leading researchers, the workshop be a combination of recent advances, with a tutorial flavor (e.g., distributed optimization, distributed control, game theory) and application areas (e.g., cyber-physical systems, energy, transportation, swarm robotics, social networks), with a forward-looking outlook. We have assembled a set of speakers whose exciting research in these areas will shed novel insights. Our deliberate selection of speakers aims to facilitate the cross-fertilization of ideas, fostering an environment conductive to the identification of open challenges in the area of network control.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:50 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>8:50 - 9:00\u003C/td>\u003Ctd colspan=\"2\">Welcome\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>9:00 - 9:45\u003C/td>\u003Ctd>Ioannis Paschalidis\u003C/td>\u003Ctd>Inverse Equilibrium Problems and Applications to Transportation Networks \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>9:45 - 10:30\u003C/td>\u003Ctd>Hideaki Ishii\u003C/td>\u003Ctd>Resilient Average Consensus via Distributed Detection and Multi-hop Communication\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>10:30 - 11:00\u003C/td>\u003Ctd colspan=\"2\">Coffee Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:00 - 11:45\u003C/td>\u003Ctd>Murat Arcak \u003C/td>\u003Ctd>Network Control Across Scales and Applications to Traffic Management\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:45 - 12:30\u003C/td>\u003Ctd>Mahnoosh Alizadeh\u003C/td>\u003Ctd>Coordination-free pricing for resource allocation over networks: models and regret guarantees\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>12:30 - 14:00\u003C/td>\u003Ctd colspan=\"2\">Lunch Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>14:00 - 14:45\u003C/td>\u003Ctd>Daniel E. Quevedo\u003C/td>\u003Ctd>Thompson Sampling for Channel Selection in Networked Estimation and Control\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>14:45 - 15:30\u003C/td>\u003Ctd>Na Li\u003C/td>\u003Ctd>Localized spectral representations for reinforcement learning in networked MDPs\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>15:30 - 16:00\u003C/td>\u003Ctd colspan=\"2\">Coffee Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16:00 - 16:45\u003C/td>\u003Ctd>Maryam Kamgarpour\u003C/td>\u003Ctd>Learning equilibria in games with bandit feedback\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>16:45 - 17:30\u003C/td>\u003Ctd>Giuseppe Notarstefano\u003C/td>\u003Ctd>System theory tools for optimization and learning in complex and distributed systems\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website:\u003C/strong> \u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/cdc24-ieee-tcns-workshop\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cu>https://sites.google.com/view/cdc24-ieee-tcns-workshop\u003C/u>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:11:37.422Z","2024-12-12T09:50:21.565Z","2024-07-20T04:11:40.860Z","101",[],"-68",{"id":383,"session":1530},{"id":383,"title":1531,"teaser":1532,"body":1533,"createdAt":1534,"updatedAt":1535,"publishedAt":1536,"url_path_id":1537,"contacts":1538,"url_path":1539},"Workshop 12: From Formal Methods to Data-Driven Verification and Control ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Abolfazl Lavaei* (Newcastle University), Chuchu Fan (Massachusetts Institute of Technology), Lars Lindemann (University of Southern California), Saber Jafarpour (University of Colorado Boulder)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Amber 8 (Floor 2)\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> Formal verification and controller synthesis for dynamical systems have garnered remarkable attention over the past two decades, driven by their extensive applications in safety-critical systems. While these formal approaches have become indispensable across numerous applications, they often necessitate closed-form mathematical models of dynamical systems. However, these models might either be unavailable or too complex to be constructed in real-world scenarios. Hence, the use of data-driven techniques becomes essential in enabling formal analysis for systems with unknown dynamics.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Over the past decade, several data-driven techniques have been proposed for the formal verification and controller synthesis of unknown dynamical systems. One may classify them in two types: the indirect and direct approaches. More specifically, indirect data-driven techniques are those which leverage system identification to learn approximate models of unknown systems, followed by model-based controller analysis approaches. In comparison, direct data-driven techniques are those that bypass the system identification phase and directly employ system measurements for the verification and controller design of unknown systems.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">In this workshop, we bring together a number of researchers active in the area of data-driven verification and control with provable guarantees. Along with cherishing the exchange of ideas between researchers in the field, by gathering a number of key talks we aim to achieve the following goals for the audience attending the workshop:\u003C/span>\u003C/p>\u003Cul>\u003Cli style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Provide to the researchers new to these topics an updated view of the state of the art on data-driven verification and control including indirect and direct data-driven techniques.\u003C/span>\u003C/li>\u003Cli style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Discuss scalable directions and areas to mitigate the, so-called, sample complexity.\u003C/span>\u003C/li>\u003Cli style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Suggest novel applications of these data-driven techniques.\u003C/span>\u003C/li>\u003C/ul>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">Additionally, we hope the active discussions of the participants will lead to fruitful collaborations.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule\u003C/strong>: 8:30 AM - 5:00 PM\u003C/span>\u003C/p>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lavaei-cps.de/workshop-CDC2024.html \">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>: \u003C/strong>\u003C/span>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lavaei-cps.de/workshop-CDC2024.html\">\u003Cspan style=\"background-color:transparent;color:#000000;\">https://lavaei-cps.de/workshop-CDC2024.html \u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:12:44.178Z","2024-10-30T22:13:43.696Z","2024-07-20T04:12:47.895Z","102",[],"-69",{"id":94,"session":1541},{"id":94,"title":1542,"teaser":1543,"body":1544,"createdAt":1545,"updatedAt":1546,"publishedAt":1547,"url_path_id":1548,"contacts":1549,"url_path":1550},"Workshop 13: Data-driven modelling, analysis, and control using the Koopman operator ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Petar Bevanda (Technical University of Munich), Sandra Hirche (Technical University of Munich), Armin Lederer (ETH Zurich), Alexandre Mauroy (University of Namur), Karl Worthmann (TU Ilmenau)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Amber 6 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>\u003Cu>Abstract\u003C/u>:\u003C/strong> The linearity of Koopman operators and the forecast simplicity of linear time-invariant (LTI) models coming from their functional representation in a space of \"observables\" lead to their increased popularity for learning dynamical systems. This representational simplicity inspired a bevy of system identification approaches and holds promise for solving many classes of nonlinear control problems through lifting nonlinear systems into suitable spaces of observables. Given that operator-theoretic system identification methods are still under active development, it is critical to present current results, main challenges and point to fruitful directions for making Koopman-based approaches more mature for systems-and-control applications.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">This workshop aims to present a broad overview of state-of-the-art Koopman operator approaches from the perspective of systems and control theory. The main objective is to provide a multifaceted perspective through an introduction to fundamental concepts, current opportunities/challenges, and recent advancements – striking a balance between a tutorial style and presenting the latest advancements.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop is organized around the following four thematic areas:\u003C/span>\u003C/p>\u003Cul>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">A tutorial introduction, (im)possibilities and dynamic mode decomposition (DMD)\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Choosing observables: from exact embeddings, and kernel methods to representation learning\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Perspectives on optimal, predictive, and robust control\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Certifiable learning and control design\u003C/span>\u003C/li>\u003C/ul>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule: \u003C/strong>8:40 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>08:40 - 8:50\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Sandra Hirche\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Welcome and opening remarks\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>8:50 – 9:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Alexandre Mauroy\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>A tutorial introduction to Koopman operator theory\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:30 – 10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Zlatko Drmač\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>Advances \u003C/i>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>in DMD – using the residuals and the Koopman-Schur decomposition\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:00 – 10:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:30 – 11:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Matthew Colbrook\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>S\u003C/i>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>pectra of Koopman operators: what is computationally (im)possible?\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:00 – 11:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Shankar A. Deka\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>I\u003C/i>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>nterpretable and verifiable learning for Lyapunov-based certificates\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:30 – 12:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Necmiye Ozay\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>P\u003C/i>\u003C/span>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>roperties of immersions for systems with multiple limit sets with implications to learning Koopman embeddings\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>12:00 – 13:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>13:30 – 14:10\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Karl Worthmann\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Control of nonlinear systems using extended dynamic mode decomposition (EDMD) with closed-loop guarantees\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:10 – 14:40\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>João Hespanha\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>Optimal control of switched Koopman models\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:40 – 15:10\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Roland Tóth\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Exact Koopman representation of nonlinear systems: from control inputs to finite dimensional embeddings\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:10 – 15:40\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:40 – 16:20\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Petar Bevanda and Armin Lederer\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:#ffffff;color:#000000;\">\u003Ci>Koopman kernels for learning dynamical systems\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:20 – 16:50\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Haruhiko Harry Asada\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Control coherent Koopman modeling: extending Koopman operator to control problems without approximation\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:50 – 17:20\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Boris Houska\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Data-driven stochastic control: exploring a PDE-constrained optimization perspective\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:20 - 17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Sandra Hirche\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Closing remarks\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://www.tu-ilmenau.de/cdc24\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003Cspan style=\"background-color:transparent;color:#000000;\"> \u003C/span>\u003C/p>","2024-07-20T04:13:47.765Z","2024-10-30T22:14:18.229Z","2024-07-20T04:13:54.951Z","103",[],"-70",{"id":98,"session":1552},{"id":98,"title":1553,"teaser":1554,"body":1555,"createdAt":1556,"updatedAt":1557,"publishedAt":1558,"url_path_id":1559,"contacts":1560,"url_path":1561},"Workshop 14: Data-driven control: theory and applications ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> M. Kanat Camlibel (U. Groningen), Jeremy Coulson (U. Wisconsin), Paolo Rapisarda (U. Southampton), Henk J. van Waarde* (U. Groningen)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Amber 7 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> Data-driven and predictive approaches are increasingly popular in control theory and its applications. Among the reasons for the predominance of data-driven perspectives in current research are the large amounts of data generated by to-be-controlled plants, the complexity of the system dynamics and the available large computational power. Each of these motivations brings with it specific challenges, for example developing efficient algorithms and dealing with uncertainties and inaccuracies. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The objective of the workshop is to provide a review of some of the origins, a critical evaluation of some aspects of the state-of-the-art, and some perspectives on current practical applications. To this purpose we plan to assemble experts in the theory and practice of data-driven and predictive control methods to present their experiences and point of views. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop is organized around the following four thematic areas:\u003C/span>\u003C/p>\u003Cul>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Behaviors and data\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Predictive control\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Uncertainty and robustness\u003C/span>\u003C/li>\u003Cli>\u003Cspan style=\"background-color:transparent;color:#000000;\">Data-driven control applications\u003C/span>\u003C/li>\u003C/ul>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop consists of 12 talks by experts in the field. There are three talks associated with each of the themes. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:50 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>8:50 - 9:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Opening\u003C/i>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>9:00 - 9:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Behavioral approach to system identification and data-driven control\u003C/i> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Ivan Markovsky and Florian Dörfler\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>9:30 - 10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Four variations on a continuous-time “fundamental lemma”\u003C/i> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Paolo Rapisarda\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>10:00 - 10:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>The shortest experiment for linear system identification \u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Kanat Camlibel, Henk van Waarde, and Paolo Rapisarda\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>10:30 - 11:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Coffee break\u003C/i>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>11:00 - 11:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Data-enabled Predictive Control\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Jeremy Coulson\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>11:30 - 12:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>A journey toward mastering Noise in Data-Driven Predictive Control: from its Subspace Origins to the Final Control Error\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Valentina Breschi\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>12:00 - 12:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Data-driven control of nonlinear systems with closed-loop stability guarantees in the Koopman framework\u003C/i> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Karl Worthmann\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>12:30 - 14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Lunch break\u003C/i>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>14:00 - 14:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>On the relations between noise, uncertainty, robustness, and performance in data-driven control and optimization\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Jaap Eising\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>14:30 - 15:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Safe Data Driven Control for nonlinear systems \u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Mario Sznaier\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>15:00 - 15:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Stochastic Data-Driven Control and Causality \u003C/i> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Timm Faulwasser\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>15:30 - 16:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Coffee break\u003C/i>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>16:00 - 16:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Data-driven control of wind energy systems\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Jan-Willem van Wingerden\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>16:30 - 17:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>The role of data-driven control in energy and power applications\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Jonathan Mayo-Maldonado\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Cstrong>17:00 - 17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">\u003Ci>Learning to Control Buildings – Towards Low-cost and Reliable Energy Management\u003C/i>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#212121;\">Colin Jones\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/rug.nl/cdc24-workshop/home\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:14:47.418Z","2024-10-30T22:14:44.740Z","2024-07-20T04:14:54.167Z","104",[],"-71",{"id":626,"session":1563},{"id":626,"title":1564,"teaser":1565,"body":1566,"createdAt":1567,"updatedAt":1568,"publishedAt":1569,"url_path_id":1570,"contacts":1571,"url_path":1572},"Workshop 15: Learning Dynamics from Data: Fusing Machine Learning and System Identification ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Yuhan Liu* (Eindhoven University of Technology), Maarten Schoukens (Eindhoven University of Technology), Roland Tóth (Eindhoven University of Technology), Dario Piga (Dalle Molle Institute for Artificial Intelligence)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Amber 3 (Floor 2)\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> \u003C/span>\u003Cspan style=\"background-color:transparent;color:#212121;\">Recent decades have witnessed significant advancements in the field of system identification. By analyzing input-output data and extracting mathematical models, system identification facilitates the characterization and prediction of dynamics, aiding in the subsequent controller design, optimization, and decision-making procedures. In traditional system identification, the focus is on learning a model of a specific system through pre-existing physical knowledge and measured input-output trajectories. This typical workflow is inextricably linked to supervised machine learning, i.e., discovering mathematical relationships in the data. Hence, we recognize that fusing system identification and machine learning presents a remarkable opportunity. This fusion enables traditional system identification to efficiently handle nonlinear systems and extend machine learning to be applicable to commonly encountered complex dynamical systems in real life. However, the challenges revolving around fusing machine learning with system identification, as evidenced by current results, primarily center on two aspects: i) lacking physical interpretation; ii) leveraging knowledge accumulated across related systems and tasks. We also focus on the opportunities that this opens in terms of “new” problems that have appeared: transfer learning, learning dynamics during reinforcement learning and model predictive control, etc.\u003C/span>\u003C/p>\u003Cp style=\"text-align:justify;\">\u003Cspan style=\"background-color:transparent;color:#212121;\">The workshop offers a repertoire of the most recent theoretical and practical developments of learning dynamical systems from data, both from the more classical system identification point of view as well as from a machine learning perspective. We also aim to cover a wide diversity of application domains, ranging from classical systems and control, to robotics, to general scientific learning. The \u003Cstrong>key topics\u003C/strong> include: i) \u003Cu>physics-informed learning\u003C/u>; ii) \u003Cu>meta-learning\u003C/u>, and iii) \u003Cu>deep neural networks\u003C/u>, with applications in i) \u003Cu>building energy systems\u003C/u>; ii) \u003Cu>electromechanical systems\u003C/u>, iii) \u003Cu>mechatronic systems\u003C/u>, etc. Beyond the presentations, ample time will be provided for discussion together with the audience. Furthermore, the workshop seeks to foster valuable interdisciplinary dialogue and collaboration between academia and industry.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:50 AM - 5:30 PM\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\"> \u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>8:50 - 9:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Welcome & Opening remarks\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:00 - 9:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>George Em Karniadakis \u003C/strong>(Brown University)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>PINNs and Deep Neural Operators for System Identification\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:45 - 10:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Thomas Beckers\u003C/strong> (Vanderbilt University)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>A Physics-Informed Composable Learning Framework\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:30 - 11:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee & Tea Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:00 - 11:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Ankush Chakrabarty\u003C/strong> (Mitsubishi Electric Research Laboratories)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Exploiting Similar Dynamics and Meta-Learning for Rapid Adaptation of Neural State-Space Models\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:45 - 12:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Dario Piga\u003C/strong> (IDSIA - Dalle Molle Institute for Artificial Intelligence Research, USI-SUPSI)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Paradigm Shift: Evolving System Identification from System Models to Class Models\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>12:30 - 14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:00 - 14:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Yuhan Liu\u003C/strong> (Eindhoven University of Technology)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Model Augmentation: From Input Design, to Model Structures and Regularized Learning\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:45 - 15:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Rajiv Singh\u003C/strong>  (Mathworks)\u003C/span>\u003C/td>\u003Ctd>Learning Nonlinear Models with MATLAB\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:30 - 16:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee & Tea Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:00 - 16:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Steve Brunton\u003C/strong> (University of Washington)\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>SINDy-RL: Interpretable and Efficient Model-based Reinforcement Learning\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:45 - 17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Panel Discussion\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://sites.google.com/view/cdc2024-mlsysid\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:15:52.577Z","2024-10-30T22:15:04.459Z","2024-07-20T04:15:57.387Z","105",[],"-72",{"id":498,"session":1574},{"id":498,"title":1575,"teaser":1576,"body":1577,"createdAt":1578,"updatedAt":1579,"publishedAt":1580,"url_path_id":1581,"contacts":1582,"url_path":1583},"Workshop 16: Remembrance of Allen Tannenbaum: Foundations of modern robust control and beyond ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Tryphon T. Georgiou* (University of California, Irvine)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 2 (Floor 2)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> On December 28, 2023, a remarkably creative academic career came to an end. Allen R. Tannenbaum left behind an astonishingly vast corpus that spans many fields, including feedback theory, optimal and robust control, signal processing, image processing and biomedical imaging, robotics, operator theory, algebraic geometry and other topics in abstract mathematics, the theory of optimal mass transport, network science, and many more. The present workshop aims to sample from this vast and diverse opus and broader related fields, focusing in particular on the field for control, to celebrate Allen's legacy and inspire the coming generation of control theorists and scientists.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Allen began his academic life in algebraic geometry, trained in pure mathematics at Harvard under Heisuke Hironaka. Over a period of almost half a century he went on to create new fields and impact science, engineering, biology and many other fields in a multitude of ways. In the late 1970's he introduced and solved the problem to optimize gain margin for linear systems using analytic interpolation theory. This foundational contribution to the field of modern robust control was a harbinger of a great chapter that began to emerge and kept the community captive throughout the 1980's, culminating in what is now known as H-infinity-control. His book on Feedback Control Theory, co-authored with John Doyle and the late Bruce Francis, nicknamed DFT, has been a standard reference for the last three decades.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">Allen pioneered the use of partial differential equations in computer vision and biomedical imaging, and the applications of Optimal Mass Transport theory to image analysis, network science, systems biology, and cancer genomic analysis. A long list of seminal contributions in the aforementioned topics and the broader field of systems and control led to transformative insights that will guide and inspire generations to come. \u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The purpose of the workshop is to celebrate the life and legacy of Allen. Those who knew personally will miss him dearly. The broader community will continue to be inspired by his work and his example. The workshop will consist of a series of talks on technical subjects by Allen's colleagues, co-workers, students and professional friends, interspersed with historical remarks and anecdotes on the ideas, influence, and science of Allen.\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">8:50-9:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Opening & Personal Remarks Rina Tannenbaum\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 1: The early years -- Allen's legacy\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">9:00-9:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Tryphon T. Georgiou\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">9:30-10:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Eduardo D. Sontag\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">10:00-10:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Mathukumali Vidyasagar\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">10:30-11:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 2: From analytic interpolation to commutant lifting theory\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">11:00-11:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Bassam Bamieh\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">11:30-12:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Malcolm C. Smith\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">12:00-12:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Hitay Özbay\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">12:30-14:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 3: Modern trends in the field\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">14:00-14:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Steve A. Morse\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">14:30-15:00 \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Mustafa Khammash\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">15:00-15:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Munzer Dahleh\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">15:30-16:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"2\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 4: Optimal transport, biology, probability, and more\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">16:00-16:20\u003C/span>\u003C/td>\u003Ctd>Anthony Yezzi\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">16:20-16:40\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Gozde Unal\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">16:40-17:00\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Peter Olver\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">17:00-17:30\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Pramod Khargonekar\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">17:30-17:40\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Remembrance and closing remarks\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website:\u003C/strong> TBD\u003C/span>\u003C/p>","2024-07-20T04:16:52.144Z","2024-11-04T03:15:05.769Z","2024-07-20T04:20:10.260Z","106",[],"-73",{"id":517,"session":1585},{"id":517,"title":1586,"teaser":1587,"body":1588,"createdAt":1589,"updatedAt":1590,"publishedAt":1591,"url_path_id":1592,"contacts":1593,"url_path":1594},"Workshop 17: Control and Adaptation: Imagine What’s Next - Celebrating the 60th Birthday of Miroslav Krstic","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Mamadou Diagne* (University of California San Diego), Nikolaos Bekiaris-Liberis (Technical University of Crete), Shuxia Tang (Texas Tech University), Huan Yu (The Hong Kong University of Science and Technology), Tiago Roux Oliveira (State University of Rio de Janeiro), Rafael Vazquez (Universidad de Sevilla), Iasson Karafyllis (National Technical University of Athens Zografou Campus)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 7 (Mezzanine/Intermediate floor)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> The workshop “Control and Adaptation: Imagine What’s Next” reviews the forefront of research on topics ranging from nonlinear control and partial differential equation (PDE) control to extremum seeking control (ESC) and games. The agenda is co-headlined by two of the most eminent scholars on these subjects: Professors Tamer Başar and Jean-Michel Coron. The first segment of the workshop covers control design methodologies for PDEs: backstepping, Lyapunov-based methods, designs for PDE-ODE interconnections, adaptive control, and flow control in various domains such as traffic, phase change in materials, and oil drilling processes. The second segment covers advances in extremum seeking and control of delay systems. Besides the exposure for students to the state of the art and historical evolution of key research subjects, the workshop will foster an atmosphere conducive to the formation of new partnerships and collaborations.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">The workshop is held on the occasion of Professor Miroslav Krstic’s 60th birthday. It celebrates his pioneering role in the creation of these research subjects and his legacy of nurturing the respective communities of researchers.\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Schedule:\u003C/strong> 8:30 AM - 6:00 PM\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 1: Control of Partial Differential Equations \u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>8:30--9:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Jean Michel Coron \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Robustness with respect to uncertainties on the velocities and the stabilization of 1-D hyperbolic systems \u003C/i> \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:00--9:25\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Rafael Vazquez \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Exploiting Symmetry in Higher-Dimensional PDE Control: A Backstepping Perspective\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:25--9:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Huan Yu \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Traffic Congestion Control by PDE Backstepping \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>9:45--10:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Jean Auriol\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Recent Contributions on the Stabilization of Networks of Hyperbolic Systems   \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">10:0-10:30\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 2: Control of Partial Differential Equations \u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>10:30--10:50\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Scott Moura \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Estimation of Battery PDE Models  \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong> 10:50--11:10\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Thomas Meurer  \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Backstepping Control for Multi-dimensional PDEs \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:10--11:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Shumon Koga\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Control of the Stefan Problem \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong> 11:30--11:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Nicolas Espitia\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Prescribed-time Control for Distributed Parameter Systems  \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>11:45--12:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Yuanyuan Shi \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Neural Operator Learning for Control: Stability and Robustness Guarantees\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">12:00-13:30\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Lunch Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 3: \u003C/strong>\u003C/span>\u003Cspan style=\"background-color:#ffffff;color:#222222;\">\u003Cstrong>Extremum seeking, Games, Adaptive, and Nonlinear Control\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>13:30--14:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Tamer Basar   \u003C/span>\u003C/td>\u003Ctd>S\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>oftly Shaping Behavior\u003C/i>       \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:00--14:25\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Iasson Karafyllis\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Robust Adaptive Control by Using Deadzone-Adapted Disturbance Suppression Control \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:25--14:45\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Nikolaos Bekiaris Liberis\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Predictor Feedback: Past/Present/Future\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>14:45--15:05\u003C/strong> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Delphine Bresch-Pietri \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Predictor Feedback for Unknown, Stochastic, and Input-Dependent Delays \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:05--15:25\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Andrey Polyakov\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Homogeneous Stabilization with Time and State Constraints \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">15:25-15:55\u003C/span>\u003C/td>\u003Ctd> \u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Coffee Break\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd colspan=\"3\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Session 4: \u003C/strong>\u003C/span>\u003Cspan style=\"background-color:#ffffff;color:#222222;\">\u003Cstrong>Extremum seeking, Games, Adaptive, and Nonlinear Control\u003C/strong>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>15:55--16:15\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Mrdjan Jankovic \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>30 Years of Collaboration, With and Without Delay\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong> 16:15--16:35\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Tiago Roux Oliveira\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci> Extremum and Nash Equilibrium Seeking through Delays and PDEs\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong> 16:35--16:55\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Jorge Poveda\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Synergies Between Optimization, Feedback, and Adaptation\u003C/i> \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>16:55--17:15\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Alexander Scheinker \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Extremum Seeking for Stabilization of Unknown Systems with Unknown Control Directions\u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:15--17:30\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Yang Zhu \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Extremum Seeking via a Time-delay Approach to Averaging  \u003C/i> \u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:30--17:45\u003C/strong> \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Ji Wang  \u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Safe Regulation of Sandwich Hyperbolic PDEs\u003C/span>\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>17:45--18:00\u003C/strong>\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">Miroslav Krstic\u003C/span>\u003C/td>\u003Ctd>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Ci>Thank you remarks \u003C/i>\u003C/span>\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp> \u003C/p>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://www.insync-lab.org/cdc2024-session\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:17:58.844Z","2024-12-11T11:19:06.101Z","2024-07-20T04:18:00.939Z","107",[],"-74",{"id":536,"session":1596},{"id":536,"title":1597,"teaser":1598,"body":1599,"createdAt":1600,"updatedAt":1601,"publishedAt":1602,"url_path_id":1603,"contacts":1604,"url_path":1605},"Workshop 18: NedicFest! A Workshop Celebrating Angelia Nedić at the CDC 2024 ","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Organizers:\u003C/strong> Cesar A. Uribe* (Rice University), Philip E. Pare (Purdue University), Thinh T. Doan (University of Texas at Austin), Soomin Lee (Amazon), Tatiana Tatarenko (Technische Universit¨at Darmstadt), Behrouz Touri (University of California San Diego), Jinming Xu (Zhejiang University), Shi Pu (The Chinese University of Hong Kong), Rasoul Etesami (University of Illinois at Urbana-Champaign), Hoi-To Wai (The Chinese University of Hong Kong), Ji Liu (Stony Brook University), Farzad Yousefian (Rutgers University)\u003C/span>\u003C/p>","\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Location:\u003C/strong> Suite 9 (Mezzanine/Intermediate floor)\u003C/span>\u003C/p>\u003Cp>\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Abstract:\u003C/strong> This workshop is being organized to celebrate Professor Angelia Nedi ́c’s 60th birthday and honor her multiple long-lasting contributions to the field of optimization and control theory. This workshop brings together 21 of her colleagues, collaborators, and former students and postdocs (including organizers and invited speakers) who will present a broad range of contemporary topics in different areas of optimization and control theory. The main goal of this workshop is to inspire a future generation of research leaders to pursue work that promotes excellence and will thus likely have a profound impact in the field.\u003C/span>\u003C/p>\u003Cfigure class=\"table\">\u003Ctable>\u003Ctbody>\u003Ctr>\u003Ctd>8:55am – 9:00am \u003C/td>\u003Ctd colspan=\"2\">Welcome Remarks\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd> 9:00am – 9:30am\u003Cbr>    \u003C/td>\u003Ctd> Emergent States in Distributed Sensing and Control\u003C/td>\u003Ctd>A. Stephen Morse\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>9:30am – 10:00am\u003C/td>\u003Ctd>Reinforcement Learning in Countable State Spaces\u003C/td>\u003Ctd>R. Srikant\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>10:00am – 11:00am \u003C/td>\u003Ctd colspan=\"2\">Coffee Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:00am – 11:30am \u003C/td>\u003Ctd>Accelerating DNN training: making multi-agent optimization outpace all-reduce\u003C/td>\u003Ctd>Mikael Johansson\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>11:30am – 12:00am\u003C/td>\u003Ctd>Machine unlearning on the spectrum: from distributed\u003Cbr>clustering to graph neural networks\u003C/td>\u003Ctd>Olgica Milenkovic\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>12:00am – 2:00pm\u003C/td>\u003Ctd colspan=\"2\">Lunch Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>2:00pm – 2:30pm\u003C/td>\u003Ctd>On the Tractable Resolution of Chance-Constrained\u003Cbr>Optimization Problems\u003C/td>\u003Ctd>Uday V. Shanbhag\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>2:30pm – 3:00pm\u003C/td>\u003Ctd>Semi-Decentralized Optimization with Collaborative Relaying\u003Cbr>in Unreliable Networks\u003C/td>\u003Ctd>Michal Yemini\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>3:00pm – 4:00pm\u003C/td>\u003Ctd colspan=\"2\">Coffee Break\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>4:00pm – 4:30pm\u003C/td>\u003Ctd>Resilient Coordination in Networked Multi-Robot Teams\u003C/td>\u003Ctd>Stephanie Gil\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>4:30pm – 5:00pm \u003C/td>\u003Ctd>Private and efficient source and channel coding approaches for distributed learning\u003C/td>\u003Ctd>Anna Scaglione\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>5:00pm – 5:30pm\u003C/td>\u003Ctd>Optimal Algorithms for Average Decentralized Consensus Computation\u003C/td>\u003Ctd>Wotao Yin\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>5:30pm – 6:00pm\u003C/td>\u003Ctd>Zeroth-Order Federated Methods for Stochastic MPECs and\u003Cbr>Nondifferentiable Nonconvex Hierarchical Optimization\u003C/td>\u003Ctd>Farzad Yousefian\u003C/td>\u003C/tr>\u003Ctr>\u003Ctd>6:00pm – 6:10pm\u003C/td>\u003Ctd colspan=\"2\"> Concluding Remarks and Group Photos \u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/figure>\u003Cp>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://cauribe.rice.edu/nedicfest2024/\">\u003Cspan style=\"background-color:transparent;color:#000000;\">\u003Cstrong>Website\u003C/strong>\u003C/span>\u003C/a>\u003C/p>","2024-07-20T04:18:48.190Z","2024-11-21T02:41:36.489Z","2024-07-20T04:18:50.900Z","108",[],"-75",{"data":1607,"meta":1608},{"id":250,"heading":251,"createdAt":252,"updatedAt":253,"publishedAt":254,"url_path_id":255,"url_path":246,"contentType":151},{},1778851174716]