Aditya Singh

PhD Student, Electrical and Systems Engineering, University of Pennsylvania

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University of Pennsylvania

Philadelphia, PA

I am a Ph.D. Student in Electrical and Systems Engineering at the University of Pennsylvania, where I am a member of the xLab advised by Prof. Rahul Mangharam. My research interests broadly lie in Safe Autonomy. More specifically, I am interested in integrating formal safety frameworks, such as Control Barrier Functions and Hamilton-Jacobi Reachability, with learning-enabled control to develop high-performance autonomous systems with provable safety guarantees. In parallel, I am also interested in uncertainty quantification to enhance the reliability and robustness of real-world autonomous systems.

Before beginning my Ph.D., I collaborated extensively with Prof. Somil Bansal at Stanford University on problems in Safe Autonomy. I also spent a wonderful one and a half years as a Research Assistant in the Stochastic Robotics Lab at the Indian Institute of Science (IISc), where I worked with Prof. Shishir Kolathaya on Safe Robot Learning.

I received my Bachelor’s degree in Electrical and Electronics Engineering from the Indian Institute of Technology (IIT) Patna in 2024, where I was advised by Prof. Sudhir Kumar. My undergraduate thesis was awarded the Institute Proficiency Prize for the Best Bachelor’s Thesis. During my undergraduate studies, I was also fortunate to receive the MITACS Globalink Research Fellowship. As a Ph.D. student at the University of Pennsylvania, I was honored to receive the Ganster Engineering Fellowship.

* indicates equal contribution on publications.

selected publications

  1. icml.png
    A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems
    M. Tayal*, A. Singh*, S. Kolathaya, and S. Bansal
    In International Conference on Machine Learning (ICML), 2025
  2. icra.png
    Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes
    A. Singh*, Z. Feng*, and S. Bansal
    In 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025
  3. cdc.png
    Semi-Supervised Safe Visuomotor Policy Synthesis using Barrier Certificates
    M. Tayal*, A. Singh*, P. Jagtap, and S. Kolathaya
    In 2025 IEEE 64th Annual Conference on Decision and Control (CDC), 2024
  4. tmlr.png
    V-OCBF: Learning Safety Filters from Offline Data via Value-Guided Offline Control Barrier Functions
    M. Tayal, M. Tayal, A. Singh, S. Kolathaya, and R. Prakash
    Transactions on Machine Learning Research (TMLR), 2025
  5. adaptnc.png
    AdaptNC: Adaptive Nonconformity Scores for Uncertainty-Aware Autonomous Systems in Dynamic Environments
    R. Tumu, A. Singh, and R. Mangharam
    In ICLR 2026 Workshop on Principled Design for Trustworthy AI, 2026