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.

Academic Appointments


Honors & Awards


  • IEEE Early Career Award in Robotics and Automation, Robotics and Automation Society (RAS) (2026)
  • CAREER Award, NSF (2022)
  • Eli Jury Award, UC Berkeley (2020)
  • RSS Pioneer, RSS (2019)
  • Outstanding Graduate Student Instructor Award, UC Berkeley (2019)

Professional Education


  • PhD, UC Berkeley, Electrical Engineering and Computer Sciences (2020)
  • MS, UC Berkeley, Electrical Engineering and Computer Sciences (2014)
  • BTech, IIT Kanpur, Electrical Engineering (2012)

Stanford Advisees


All Publications


  • Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection IEEE ROBOTICS AND AUTOMATION LETTERS Qiu, L., Ciftci, Y., Bansal, S. 2026; 11 (6): 7222-7229
  • Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators IEEE ROBOTICS AND AUTOMATION LETTERS Chakraborty, K., Feng, Z., Veer, S., Sharma, A., Ding, W., Topan, S., Ivanovic, B., Pavone, M., Bansal, S. 2026; 11 (3): 3262-3269
  • One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environments IEEE TRANSACTIONS ON ROBOTICS Lin, A., Peng, S., Bansal, S. 2026; 42: 545-560
  • DualGuard MPPI: Safe and Performant Optimal Control by Combining Sampling-Based MPC and Hamilton-Jacobi Reachability IEEE ROBOTICS AND AUTOMATION LETTERS Borquez, J., Raus, L., Ciftci, Y., Bansal, S. 2025; 10 (7): 6944-6951
  • Stable-BC: Controlling Covariate Shift With Stable Behavior Cloning IEEE ROBOTICS AND AUTOMATION LETTERS Mehta, S. A., Ciftci, Y., Ramachandran, B., Bansal, S., Losey, D. P. 2025; 10 (2): 1952-1959
  • A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems Tayal, M., Singh, A., Kolathaya, S., Bansal, S. edited by Singh, A., Fazel, M., Hsu, D., Lacoste-Julien, S., Berkenkamp, F., Maharaj, T., Wagstaff, K., Zhu, J. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2025: 59237-59258
  • Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games Sharpless, W., Feng, Z., Bansal, S., Herbert, S. edited by Ozay, N., Balzano, L., Panagou, D., Abate, A. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2025: 365-377
  • Updating Robot Safety Representations Online from Natural Language Feedback Santos, L., Li, Z., Peters, L., Bansal, S., Bajcsy, A. edited by Ott, C. IEEE. 2025: 7778-7785
  • System-Level Safety Monitoring and Recovery for Perception Failures in Autonomous Vehicles Chakraborty, K., Feng, Z., Veer, S., Sharma, A., Ivanovic, B., Pavone, M., Bansal, S. edited by Ott, C. IEEE. 2025: 12885-12891
  • Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes Singh, A., Feng, Z., Bansal, S. edited by Ott, C. IEEE. 2025: 5489-5495
  • Reachability Analysis for Black-Box Dynamical Systems Chilakamarri, V., Feng, Z., Bansal, S. edited by Ott, C. IEEE. 2025: 3552-3558
  • SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems Ciftci, Y., Chiu, D., Feng, Z., Sukhatme, G. S., Bansal, S. edited by Ott, C. IEEE. 2025: 3559-3566
  • Providing Safety Assurances for Systems With Unknown Dynamics IEEE CONTROL SYSTEMS LETTERS Wang, H., Borquez, J., Bansal, S. 2024; 8: 1108-1113
  • Verification of Neural Reachable Tubes via Scenario Optimization and Conformal Prediction Lin, A., Bansal, S. edited by Abate, A., Cannon, M., Margellos, K., Papachristodoulou, A. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2024: 719-731
  • Parameterized Fast and Safe Tracking (FaSTrack) using DeepReach Jeong, H., Gong, Z., Bansal, S., Herbert, S. edited by Abate, A., Cannon, M., Margellos, K., Papachristodoulou, A. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2024: 1006-1017
  • Cooptimizing Safety and Performance With a Control-Constrained Formulation IEEE CONTROL SYSTEMS LETTERS Wang, H., Dhande, A., Bansal, S. 2024; 8: 2739-2744
  • Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers Gupta, A., Chakraborty, K., Bansal, O., IEEE IEEE. 2024: 9953-9959
  • On Safety and Liveness Filtering Using Hamilton-Jacobi Reachability Analysis IEEE TRANSACTIONS ON ROBOTICS Borquez, J., Chakraborty, K., Wang, H., Bansal, S. 2024; 40: 4235-4251
  • Discovering Closed-Loop Failures of Vision-Based Controllers via Reachability Analysis IEEE ROBOTICS AND AUTOMATION LETTERS Chakraborty, K., Bansal, S. 2023; 8 (5): 2692-2699
  • Parameter-Conditioned Reachable Sets for Updating Safety Assurances Online Borquez, J., Nakamura, K., Bansal, S., IEEE IEEE. 2023: 10553-10559
  • Generating Formal Safety Assurances for High-Dimensional Reachability Lin, A., Bansal, S., IEEE IEEE. 2023: 10525-10531
  • Online Update of Safety Assurances Using Confidence-Based Predictions Nakamura, K., Bansal, S., IEEE IEEE. 2023: 12765-12771
  • Computation of Regions of Attraction for Hybrid Limit Cycles Using Reachability: An Application to Walking Robots IEEE ROBOTICS AND AUTOMATION LETTERS Choi, J. J., Agrawal, A., Sreenath, K., Tomlin, C. J., Bansal, S. 2022; 7 (2): 4504-4511
  • FaSTrack:A Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking IEEE TRANSACTIONS ON AUTOMATIC CONTROL Chen, M., Herbert, S. L., Hu, H., Pu, Y., Fisac, J., Bansal, S., Han, S., Tomlin, C. J. 2021; 66 (12): 5861-5876
  • Provably Safe and Scalable Multivehicle Trajectory Planning IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY Bansal, S., Chen, M., Tanabe, K., Tomlin, C. J. 2021; 29 (6): 2473-2489
  • Visual Navigation Among Humans With Optimal Control as a Supervisor IEEE ROBOTICS AND AUTOMATION LETTERS Tolani, V., Bansal, S., Faust, A., Tomlin, C. 2021; 6 (2): 2288-2295
  • DeepReach: A Deep Learning Approach to High-Dimensional Reachability Bansal, S., Tomlin, C. J., IEEE IEEE. 2021: 1817-1824
  • A Robust Control Framework for Human Motion Prediction IEEE ROBOTICS AND AUTOMATION LETTERS Bajcsy, A., Bansal, S., Ratner, E., Tomlin, C. J., Dragan, A. D. 2021; 6 (1): 24-31
  • A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning Bansal, S., Bajcsy, A., Ratner, E., Dragan, A. D., Tomlin, C. J., IEEE IEEE. 2020: 7149-7155
  • Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability Li, A., Bansal, S., Giovanis, G., Tolani, V., Tomlin, C., Chen, M. edited by Jadbabaie, A., Pappas, G., Parrilo, P. A., Recht, B., Tomlin, C., Zeilinger, M., Bayen, A. M. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2020: 500-510
  • Robust Sequential Trajectory Planning Under Disturbances and Adversarial Intruder IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY Chen, M., Bansal, S., Fisac, J. F., Tomlin, C. J. 2019; 27 (4): 1566–82
  • Plug-and-Play Model Predictive Control for Load Shaping and Voltage Control in Smart Grids IEEE TRANSACTIONS ON SMART GRID Le Floch, C., Bansal, S., Tomlin, C. J., Moura, S. J., Zeilinger, M. N. 2019; 10 (3): 2334-2344
  • Reachability-Based Safety Guarantees using Efficient Initializations Herbert, S. L., Bansal, S., Ghosh, S., Tomlin, C. J., IEEE IEEE. 2019: 4810-4816
  • Closed-loop Model Selection for Kernel-based Models using Bayesian Optimization Beckers, T., Bansal, S., Tomlin, C. J., Hirche, S., IEEE IEEE. 2019: 828-834
  • An Efficient Reachability-Based Framework for Provably Safe Autonomous Navigation in Unknown Environments Bajcsy, A., Bansal, S., Bronstein, E., Tolani, V., Tomlin, C. J., IEEE IEEE. 2019: 1758-1765
  • A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics Ghosh, S., Bansal, S., Sangiovanni-Vincentelli, A., Seshia, S. A., Tomlin, C., ACM ASSOC COMPUTING MACHINERY. 2019: 185-196
  • Decomposition of Reachable Sets and Tubes for a Class of Nonlinear Systems IEEE TRANSACTIONS ON AUTOMATIC CONTROL Chen, M., Herbert, S. L., Vashishtha, M. S., Bansal, S., Tomlin, C. J. 2018; 63 (11): 3675-3688
  • Safe Sequential Path Planning Under Disturbances and Imperfect Information Bansal, S., Chen, M., Fisac, J. F., Tomlin, C. J., IEEE IEEE. 2017: 5550-5555
  • FaSTrack: a Modular Framework for Fast and Guaranteed Safe Motion Planning Herbert, S. L., Chen, M., Han, S., Bansal, S., Fisac, J. F., Tomlin, C. J., IEEE IEEE. 2017
  • Hamilton-Jacobi Reachability: A Brief Overview and Recent Advances Bansal, S., Chen, M., Herbert, S., Tomlin, C. J., IEEE IEEE. 2017
  • Learning Quadrotor Dynamics Using Neural Network for Flight Control Bansal, S., Akametalu, A. K., Jiang, F. J., Laine, F., Tomlin, C. J., IEEE IEEE. 2016: 4653-4660