David Fridovich-Keil

Biography

Dr. Fridovich-Keil joined the University as an assistant professor in Fall 2021. He received his doctorate from the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, where he developed some of the first efficient techniques for solving noncooperative, game-theoretic motion planning problems. Dr. Fridovich-Keil was a postdoctoral scholar in the Department of Aeronautics and Astronautics at Stanford University, where his research focused on exploiting computational parallelism in stochastic optimal control problems.

Dr. Fridovich-Keil’s research spans optimal control, dynamic game theory, learning for control and robot safety. While he has also worked on problems in distributed control, reinforcement learning, and active search, he is currently investigating the role of dynamic game theory in multi-agent interactive settings such as traffic. Fridovich-Keil’s work also focuses on the interplay between machine learning and classical ideas from robust, adaptive, and geometric control theory.

NSF Graduate Research Fellowships Program, 2015

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