Negar Mehr

Negar Mehr is a robotics researcher who uses control theory, game theory and machine learning to help autonomous systems interact safely with people and other robots. She earned mechanical engineering degrees at Sharif University of Technology in 2013 and UC Berkeley in 2019, then worked as a postdoctoral scholar in Stanford’s Department of Aeronautics and Astronautics from 2019 to 2020. After joining Illinois’s aerospace engineering faculty in 2020, she received an NSF CAREER Award in 2022 to study traffic shared by human-driven and autonomous cars. Her coauthored papers include Potential iLQR in 2021 and Maximum-Entropy Multi-Agent Dynamic Games in 2023. Since January 2024, she is an assistant professor of mechanical engineering at UC Berkeley, where she runs the ICON Lab; she also holds an adjunct professor appointment in aerospace engineering at Illinois.

Now at: University of California, Berkeley and University of Illinois Urbana-Champaign
Works: 73
Citations: 537
h-index: 13
Badges: Boomerang

Publication numbers from OpenAlex, as of 28 October 2026.

Timeline

2013–2019

Mechanical engineering degrees

She earns a bachelor’s degree in mechanical engineering at Sharif University of Technology in 2013 and a PhD in mechanical engineering at UC Berkeley in 2019.
2019–2020

Postdoctoral work at Stanford

From 2019 to 2020, she is a postdoctoral scholar in Stanford University’s Department of Aeronautics and Astronautics.
2020

Joining aerospace engineering at Illinois

In 2020, she joins the faculty of the Department of Aerospace Engineering at the University of Illinois Urbana-Champaign as an assistant professor. She wins first prize in the IEEE Intelligent Transportation Systems Society’s Best PhD Dissertation Award in 2020.
2021

The Potential iLQR controller

With Talha Kavuncu and Ayberk Yaraneri, she coauthors “Potential iLQR: A Potential-Minimizing Controller for Planning Multi-Agent Interactive Trajectories” at Robotics: Science and Systems in 2021. The method plans interactions among multiple agents by solving a single optimal control problem for a class of differential games.
2022

An NSF CAREER Award

In 2022, she receives an NSF CAREER Award to study traffic networks shared by human-driven and autonomous cars. The project examines routing decisions, human incentives and infrastructure planning to improve mobility.
2023

Maximum-entropy dynamic games

In 2023, she coauthors “Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions” with Mingyu Wang, Maulik Bhatt and Mac Schwager in IEEE Transactions on Robotics. The paper defines an entropic cost equilibrium for agents with limited rationality and develops methods to infer their cost functions from observed interactions.
January 2024

Returning to Berkeley

In January 2024, she joins UC Berkeley’s Department of Mechanical Engineering as an assistant professor.
2026

An ONR investigator award

She receives the Office of Naval Research’s Young Investigator Program Award in 2026.
As of October 2026

Berkeley and Illinois appointments

As of October 2026, she is an assistant professor in UC Berkeley’s Department of Mechanical Engineering and runs the Berkeley Intelligent Control (ICON) Lab. Her work uses control theory, robotics, game theory and machine learning to help autonomous systems interact safely with people and other robots. She also holds an adjunct professor appointment in the Department of Aerospace Engineering at the University of Illinois Urbana-Champaign.