Building Certifiably Safe and Correct Large-Scale Autonomous Systems - Chuchu Fan

Institute for Assured Autonomy & Computer Science Seminar Series
October 18, 2022
“Building Certifiably Safe and Correct Large-Scale Autonomous Systems”
Chuchu Fan, Massachusetts Institute of Technology
The introduction of machine learning and artificial intelligence creates unprecedented opportunities for achieving full autonomy. However, learning-based methods in building autonomous systems can be extremely brittle in practice and are not designed to be verifiable. In this talk, Chuchu Fan will present several of her recent efforts that combine ML with formal methods and control theory to enable the design of provably dependable and safe autonomous systems. She will introduce techniques to generate safety certificates and certified decision and control for complex autonomous systems, even when the systems have many agents, follow nonlinear and nonholonomic dynamics, and need to satisfy high-level specifications.
Chuchu Fan is an assistant professor in the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology. Before that, she was a postdoctoral researcher at the California Institute of Technology. Fan received her PhD in 2019 from the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. She earned her bachelor’s degree from Tsinghua University’s Department of Automation. Fan's group at MIT works on using rigorous mathematics-including formal methods, machine learning, and control theory-for the design, analysis, and verification of safe autonomous systems. Her dissertation, “Formal Methods forSafe Autonomy,” won the ACM Doctoral Dissertation Award in 2020.