Rate My Professor Negar Mehr

Mehr's research interests lie at the intersection of robotics, control theory, game theory, and machine learning. She develops algorithms and mathematical models enabling autonomous systems to interact safely and intelligently with humans and other agents in unstructured environments. Her work has applications in space exploration, autonomous driving, unmanned aerial vehicles, and assistive robots. She has published in leading journals and conferences, including IEEE Transactions on Robotics, IEEE Robotics and Automation Letters, IEEE Transactions on Control of Network Systems, Robotics: Science and Systems, and IEEE/RSJ International Conference on Intelligent Robots and Systems. Notable publications include “Maximum-entropy multi-agent dynamic games: Forward and inverse solutions” (Mehr et al., 2023, IEEE Transactions on Robotics), “How will the presence of autonomous vehicles affect the equilibrium state of traffic networks?” (Mehr and Horowitz, 2019, IEEE Transactions on Control of Network Systems), “Potential iLQR: A potential-minimizing controller for planning multi-agent interactive trajectories” (Kavuncu et al., 2021, Robotics: Science and Systems), “Game-theoretic planning for risk-aware interactive agents” (Wang et al., 2020, IEEE/RSJ IROS), and “Learning contraction policies from offline data” (Rezazadeh et al., 2022, IEEE Robotics and Automation Letters). Mehr is a recipient of the NSF CAREER Award and the 2020 IEEE Intelligent Transportation Systems Best Ph.D. Dissertation Award. She has been recognized as a Rising Star in EECS, Aeronautics and Astronautics, and Civil and Environmental Engineering.