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You are here: Home / People / Negar Mehr

Negar Mehr

Assistant Professor of Mechanical Engineering
(January 2024)

Etcheverry Hall
University of California, Berkeley
Berkeley, CA 94720-1740
negar@berkeley.edu

For more information see: Dr. Mehr's Website

Dr. Negar Mehr will join the Department of Mechanical Engineering at the University of California, Berkeley in January of 2024. She is currently an assistant professor of Aerospace Engineering at the University of Illinois Urbana-Champaign. She is also affiliated with the Coordinated Science Laboratory (CSL) and Electrical and Computer Engineering department at UIUC. Previously, she was a postdoctoral scholar at Stanford Aeronautics and Astronautics department from 2019 to 2020. She received her Ph.D. in Mechanical Engineering from UC Berkeley in 2019 and her B.Sc. in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, in 2013. She is a recipient of the NSF CAREER Award. She was awarded the IEEE Intelligent Transportation Systems best Ph.D. dissertation award in 2020. Negar was recognized as a rising star in EECS, Aeronautics & Astronautics, and Civil and Environmental Engineering.


Research Description:

Dr. Mehr’s research focuses on creating algorithms and mathematical models for autonomous systems to interact safely and intelligently with humans and other autonomous systems. As AI advances, robots can handle more complex tasks, and the key to unlocking their full potential lies in their ability to operate safely and intelligently in unstructured environments alongside other agents. Dr. Mehr’s group aims to equip robots with such capabilities. Her research interests lie at the intersection of robotics, control theory, game theory, and machine learning. She has published in top robotics and control journals and conferences. Her research has had applications in various domains including space exploration, autonomous driving, UAVs, and assistive robots. She runs the Intelligent Control (ICON) lab where her group utilizes robotic hardware for verifying and testing their developed control algorithms.

Key Publications:

Mehr, N., Wang, M., Bhatt, M., & Schwager, M. (2023). Maximum-entropy multi-agent dynamic games: Forward and inverse solutions. IEEE Transactions on Robotics. https://doi.org/10.1109/TRO.2022.3232300 
 
Rezazadeh, N., Kolarich, M., Kia, S. S., & Mehr, N. (2022). Learning contraction policies from offline data. IEEE Robotics and Automation Letters, 7(2), 2905-2912. https://doi.org/10.1109/LRA.2022.3145100 
 
Kavuncu, T., Yaraneri, A., & Mehr, N. (2021, July). Potential iLQR: A potential-minimizing controller for planning multi-agent interactive trajectories. In proceedings of 2021 Robotics: Science and Systems (RSS). https://www.roboticsproceedings.org/rss17/p084.html
 
Nishimura, H., Mehr, N., Gaidon, A., & Schwager, M. (2021). RAT iLQR: A risk auto-tuning controller to optimally account for stochastic model mismatch. IEEE Robotics and Automation Letters, 6(2), 763-770. https://doi.org/10.1109/LRA.2020.3048660
 
Wang, M., Mehr, N., Gaidon, A., & Schwager, M. (2020, October). Game-theoretic planning for risk-aware interactive agents. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6998-7005). IEEE. https://doi.org/10.1109/IROS45743.2020.9341137
 
Mehr, N., & Horowitz, R. (2019). How will the presence of autonomous vehicles affect the equilibrium state of traffic networks?. IEEE Transactions on Control of Network Systems, 7(1), 96-105. https://doi.org/10.1109/TCNS.2019.2918682

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