Education
- Postdoctoral Scholar, Stanford University, 2021-2023
- Ph.D., University of California, Berkeley, 2021
- B.S., Harbin Institute of Technology, 2016
Teaching Interests
Professor Li’s teaching interests span artificial intelligence, robotics, autonomy, control, and human-centered systems engineering, with an emphasis on developing trustworthy intelligent systems that can safely and effectively operate in complex, human-centered environments. His courses integrate foundational topics in machine learning, optimization, control, perception, and decision making with emerging advances in robot learning and embodied AI. He emphasizes connecting rigorous theoretical foundations with hands-on projects and real-world applications in robotics and autonomous systems. Through interdisciplinary and project-based learning, Professor Li aims to equip students with the analytical, computational, and system-level skills needed to design the next generation of safe, reliable, and intelligent autonomous systems.
Research Interests
Professor Li’s research aims to enable trustworthy, interactive, and human-centered embodied intelligence that can perceive, understand, and reason about the physical world; safely interact and collaborate with humans; and effectively coordinate with other intelligent agents to benefit society in everyday life. Toward this vision, his group pursues interdisciplinary research that develops fundamental theories and practical algorithms at the intersection of robotics, trustworthy AI/ML, reinforcement learning, computer vision, control, and optimization. His research particularly focuses on safe robot learning, human-robot interaction, and multi-agent systems, with methods extensively validated on diverse robotic platforms, including humanoids, mobile manipulators, quadrupeds, autonomous vehicles, robotic manipulators, and aerial robots. Graduate and undergraduate students are actively involved in the theoretical, computational, and experimental aspects of his research. More information is available on his lab website.
Recent Publications
- Z. Wang, H. Jiang, S. Dong, Y. Wang, H. Qiu, and J. Li, "Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
- J. Yao, X. Zhang, Y. Xia, Z. Wang, A. K. Roy-Chowdhury, and J. Li, "Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty Handling", Conference on Robot Learning (CoRL), 2025.
- X. Zhang*, H. Qin*, F. Wang, Y. Dong, and J. Li, "LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner", International Conference on Robotics and Automation (ICRA), 2025.
- M. Yan, Y. Wang, Z. Liu, and J. Li, "RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Tasks", Advances in Neural Information Processing Systems (NeurIPS), 2025.
- J. Li, D. Isele, K. Lee, J. Park, K. Fujimura, and M. J. Kochenderfer, "Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation", IEEE Transactions on Robotics (T-RO), 2024.