ECE Departmental Seminar
Building Dependable Autonomous Systems through Learning Certified Decisions and Control
Dr. Chuchu Fan
Massachusetts Institute of Technology
Friday, 12/3/21, 11:00am
To obtain access the Zoom link for this seminar, please click here to register.
Abstract: The introduction of machine learning (ML) and artificial intelligence (AI) 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, I will present our recent progress on combining ML with formal methods and control theory to enable the design of provably dependable and safe autonomous systems. I will introduce our techniques to generate safety certificates and certified decision and control for complex autonomous systems, even when the systems have multiple agents, follow nonlinear and nonholonomic dynamics, and need to satisfy high-level specifications.
Bio: Chuchu Fan is the Wilson assistant professor of Aeronautics and Astronautics at MIT. Before joining MIT in 2020, she was a postdoctoral researcher in the Department of Computing and Mathematical Sciences at the California Institute of Technology. She received her Ph.D. in 2019 from the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, and her Bachelor's degree from Tsinghua University in 2013. She is currently leading the reliable autonomous system lab (Realm Lab) at MIT. Her group studies how to use rigorous mathematics, including formal methods, machine learning, and control theory for the design, analysis, and verification of safe autonomous systems. She is the recipient of the 2020 ACM Doctoral Dissertation Award.