Somil Bansal
Assistant Professor of Aeronautics and Astronautics
Bio
Somil Bansal is an assistant professor at the Department of Aeronautics and Astronautics at Stanford. Before joining Stanford, he was an assistant professor in the ECE department at the University of Southern California. He received an MS and a Ph.D. in Electrical Engineering and Computer Sciences (EECS) from the University of California at Berkeley in 2014 and 2020, respectively. Before that, he obtained a B.Tech. in Electrical Engineering from the Indian Institute of Technology, Kanpur in 2012. After his PhD, he spent a year as a Research Scientist at Waymo (formerly known as the Google Self-Driving Car project). He has also collaborated closely with companies like Skydio, Google, Boeing, as well as NASA AMES/JPL. Somil is broadly interested in developing mathematical tools and algorithms for the control and analysis of safety-critical autonomous and robotic systems, with a special emphasis on ensuring the safety of learning-enabled systems. Somil has received several awards, most notably the NSF CAREER award, the Eli Jury Award at UC Berkeley for his doctoral research, the RSS Pioneer Award, and the Outstanding Graduate Student Instructor Award.
Honors & Awards
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CAREER Award, NSF (2022)
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Eli Jury Award, UC Berkeley (2020)
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RSS Pioneer, RSS (2019)
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Outstanding Graduate Student Instructor Award, UC Berkeley (2019)
Professional Education
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PhD, UC Berkeley, Electrical Engineering and Computer Sciences (2020)
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MS, UC Berkeley, Electrical Engineering and Computer Sciences (2014)
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BTech, IIT Kanpur, Electrical Engineering (2012)
All Publications
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Providing Safety Assurances for Systems With Unknown Dynamics
IEEE CONTROL SYSTEMS LETTERS
2024; 8: 1108-1113
View details for DOI 10.1109/LCSYS.2024.3408069
View details for Web of Science ID 001251152400019
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On Safety and Liveness Filtering Using Hamilton-Jacobi Reachability Analysis
IEEE TRANSACTIONS ON ROBOTICS
2024; 40: 4235-4251
View details for DOI 10.1109/TRO.2024.3454470
View details for Web of Science ID 001317680300003
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Provably Safe and Scalable Multivehicle Trajectory Planning
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
2021; 29 (6): 2473-2489
View details for DOI 10.1109/TCST.2020.3042815
View details for Web of Science ID 000704824600018
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Visual Navigation Among Humans With Optimal Control as a Supervisor
IEEE ROBOTICS AND AUTOMATION LETTERS
2021; 6 (2): 2288-2295
View details for DOI 10.1109/LRA.2021.3060638
View details for Web of Science ID 000631202300003
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A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
IEEE. 2020: 7149-7155
View details for DOI 10.1109/icra40945.2020.9197257
View details for Web of Science ID 000712319504113
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Robust Sequential Trajectory Planning Under Disturbances and Adversarial Intruder
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
2019; 27 (4): 1566–82
View details for DOI 10.1109/TCST.2018.2828380
View details for Web of Science ID 000471717100014
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Reachability-Based Safety Guarantees using Efficient Initializations
IEEE. 2019: 4810-4816
View details for Web of Science ID 000560779004067
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Closed-loop Model Selection for Kernel-based Models using Bayesian Optimization
IEEE. 2019: 828-834
View details for Web of Science ID 000560779000126