David Fridovich-Keil

David Fridovich-Keil is an Assistant Professor in the Department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin, where he joined in Fall 2021. His research spans optimal control, dynamic game theory, and robot safety with a focus on multi-agent interactive settings like traffic.

Education:

• Ph.D., University of California, Berkeley

His research integrates machine learning with classical control theory for robust autonomous systems, emphasizing motion planning and safety in multi-agent decision making. Current work explores dynamic game theory applications in traffic scenarios, building on foundational contributions to noncooperative game-theoretic motion planning.

Scientific Awards:

• National Science Foundation CAREER Award (2024)

Dr. Fridovich-Keil leads the Fridovich-Keil Lab, conducting NSF-funded research on computational parallelism in stochastic optimal control. His industry experience includes a stint at self-driving car company Nuro during doctoral studies, bridging academic theory with real-world autonomy challenges.