Plenary Speakers

Schedule: Thursday, December 19, 8:30-9:30
Location: Auditorium

Semper in motu: Transforming mobility through learning and control

The transformation of the transport sector is continuously in motion. Through advances in sensing, connectivity, computing, and electrification, the control community has been, and will continue to be, actively engaged in shaping a sustainable and efficient infrastructure for moving people and goods. While self-driving technologies have garnered significant attention, achieving widespread, safe deployment remains a challenge. Meanwhile, innovations in optimizing and enhancing the resilience of transport systems continue to advance, highlighting the broader impact of control technology on mobility. This lecture will explore the emerging field of learning-enabled cyber-physical-human systems and discuss some specific examples in intelligent transport. We will show how connected vehicles acting as mobile sensors and actuators can enable traffic predictions and control at a scale never before possible, by learning traffic models using physics-informed machine learning techniques. The complexities of safe interactions between automated and human-driven vehicles will be discussed, emphasizing the integration of formal reasoning methods and the use of tele-operation. The presentation highlights joint work with students, postdocs, and collaborators in academia and industry.

Schedule: Monday, December 16, 8:30-9:30
Location: Auditorium

Ask not what AI can do for control, ask what control can do for AI

AI has drastically changed the landscape of several engineering disciplines, such as computer vision and natural language processing, and is now an integral part of several commercial products. In this talk I will argue, through several vignettes, that ideas and techniques from control can help answer fundamental questions about the power, limitations, and societal impact of AI.

Schedule: Tuesday, December 17, 8:30-9:30
Location: Auditorium

Towards Safe and Resilient Autonomy Using Synergistic Control, Observation and Learning

Enabling autonomy for robotic and cyber-physical systems with provable safety and resilience guarantees has been an ongoing area of research. Despite significant progress over the years, there are still open challenges due to constraints (e.g., safety and time specifications; sensing, computation and communication limitations), and environmental uncertainty. This plenary talk will present some of our recent results and ongoing work on a framework that interconnects control, planning and learning methods towards provably-correct safety-critical robotic and aerospace systems under constraints and uncertainty.

Schedule: Wednesday, December 18, 8:30-9:30
Location: Auditorium

From Dissipativity to the Design of Controllers for Optimization

Recent years have witnessed a renewed interest in considering optimization algorithms as feedback systems. This viewpoint turns, for example, the analysis of the convergence properties of a first order algorithm into a problem of stability analysis of a Lur'e system. In this talk we highlight why dissipativity plays a key role for developing unprecedented tools to analyze the convergence properties of first order algorithms for solving convex programs. In contrast to alternative approaches, we reveal that the proposed avenue permits not only the analysis but also the systematic design of optimization algorithms using convex semi-definite programming. We substantiate that the proposed tools form a promising ingredient of a system theory for the design of controllers for optimization.