ASSET Seminar: The marriage of logic and learning: will it be a happily ever after? (Jyotirmoy Deshmukh, University of Southern California)

Presentation Abstract: 

Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of such CPS applications is that they are safety-critical: any undesirable behavior by such systems can cause serious harm to human lives or property. The formal methods community has been an advocate of using logic and automata as specifications for safety-critical CPSs, and the past few decades have seen significant strides in algorithms for their verification, testing, and automated synthesis. A new challenge now is the presence of learning-enabled components (LECs) in CPSs, and in this talk, we will review some recent work on using logic and learning-based techniques to provide guarantees for CPS applications using LECs. The happiness of this marriage between logic and learning depends on the applicability and scalability of these techniques to real-world systems; we will discuss success stories as well as challenges that need to be solved.

Speaker Bio:

Jyotirmoy V. Deshmukh (Jyo) is an Assistant Professor in the Department of Computer Science at the University of Southern California, and the co-Director of the Center for Autonomy and AI. Before joining USC, Jyo worked as a Principal Research Engineer at Toyota R&D. He got his Ph.D. from the University of Texas at Austin in 2010 and was a postdoctoral research fellow at the University of Pennsylvania. He is the recipient of the 2021 NSF Career Award and the 2021 Amazon Research Award.