Kehan Long

I work on robotics at SceniX AI.

I received my Ph.D. in Mathematics from University of California San Diego, where I worked on robotics and was fortunate to be advised by Nikolay Atanasov, Jorge Cortés, and Melvin Leok. I received my B.S. in Applied Mathematics from University of Illinois, Urbana-Champaign.

Email  /  Google Scholar  /  Github  /  LinkedIn

Research Interests

My research lies at the intersection of robotics, artificial intelligence, and control theory, with a focus on enabling reliable robot autonomy. I develop methods for robot learning and control, decision-making under uncertainty, and safe robot autonomy, combining theoretical insights with practical applicability for real-world robotic systems.

News

[09/2025] Our paper on Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions has been accepted to NeurIPS 2025.
[09/2025] I successfully defended my PhD dissertation on "Certifiable Robot Control under Uncertainty: Towards Safety, Stability, and Robustness"!
[07/2025] Our paper on Neural Configuration Distance Function for Continuum Robot Control has been accepted to IROS 2025.
[05/2025] Our paper on Sensor-based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments has been accepted to IJRR.
[04/2025] I am honored to be selected as RSS Pioneers 2025 for my work on Certifiable Robot Autonomy under Uncertainty!
[08/2024] Our paper on Distributionally Robust Policy and Lyapunov-Certificate Learning has been accepted to IEEE OJ-CSYS.
[07/2024] Our paper on Stabilization of Nonlinear Systems through Control Barrier Functions has been accepted to CDC 2024.
[01/2024] Our paper on Safe Stabilizing Control for Polygonal Robots in Dynamic Elliptical Environments has been accepted to ACC 2024.
[12/2023] Our paper on Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers has been accepted to L-CSS.
[03/2023] Our paper on Distributionally Robust Lyapunov Function Search Under Uncertainty has been accepted to L4DC 2023.
[01/2023] Our paper on Safe and Stable Control Synthesis for Uncertain System Models via Distributionally Robust Optimization has been accepted to ACC 2023.
[06/2022] Our paper on Safe Control Synthesis with Uncertain Dynamics and Constraints has been accepted to RA-L with IROS 2022.
[03/2021] Our paper on Learning Barrier Functions with Memory for Robust Safe Navigation has been accepted to RA-L with ICRA 2021. 🎉🎉🎉

Selected Publications

• Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
  Kehan Long, Jorge Cortés, Nikolay Atanasov
  Advances in Neural Information Processing Systems (NeurIPS), 2025
  arXiv code bibtex
• Neural Configuration-Space Barriers for Manipulation Planning and Control
  Kehan Long, Ki Myung Brian Lee, Nikola Raicevic, Niyas Attasseri, Melvin Leok, Nikolay Atanasov
  arXiv Preprint, 2025
  project page arXiv code bibtex
• Neural Configuration Distance Function for Continuum Robot Control
  Kehan Long, Hardik Parwana, Georgios Fainekos, Bardh Hoxha, Hideki Okamoto, Nikolay Atanasov
  IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025
  arXiv code bibtex
• Sensor-Based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments
  Kehan Long, Yinzhuang Yi, Zhirui Dai, Sylvia Herbert, Jorge Cortés, Nikolay Atanasov
  International Journal of Robotics Research (IJRR), 2025
  project page arXiv code bibtex
• Safe Control Synthesis With Uncertain Dynamics and Constraints
  Kehan Long, Vikas Dhiman, Melvin Leok, Jorge Cortés, Nikolay Atanasov
  IEEE Robotics and Automation Letters (RA-L), 2022
  arXiv bibtex
• Learning Barrier Functions With Memory for Robust Safe Navigation
  Kehan Long, Cheng Qian, Jorge Cortés, Nikolay Atanasov
  IEEE Robotics and Automation Letters (RA-L), 2021
  arXiv bibtex

Contact

You are very welcome to contact me regarding my research and collaboration. I can be contacted directly at kehan.lkh@gmail.com