Jiachen Li is a Coca-Cola Foundation Early Career Professor and Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) and the George W. Woodruff School of Mechanical Engineering (ME) at Georgia Tech. He leads the Trustworthy Autonomous Systems Laboratory (TASL). Before joining Georgia Tech, he received his Ph.D. from the University of California, Berkeley, followed by a Postdoctoral Scholar appointment at Stanford University. Dr. Li was recognized an RSS Robotics Pioneer and an ASME DSCD Rising Star. He currently serves as Co-Chair of the IEEE RAS Technical Committee on Robot Learning and as an Associate Editor or Area Chair for more than ten leading journals and conferences. 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, foundation models, reinforcement learning, computer vision, control, and optimization, with particularly focuses on safe robot learning, human-robot interaction, and multi-agent systems, with methods extensively validated on a wide range of real-world robotic platforms.
- AI/ML for Robotics
- Collaborative Robotics
- Field and Service Robotics
- Science of Robotics
- Robot Learning for Navigation and (Mobile) Manipulation
- Trustworthy Embodied/Physical AI (e.g., Safety, Robustness, Generalizability, Explainability, Verification)
- Foundation Models & Agentic AI
- Deep Reinforcement Learning & Sequential Decision Making & Controls
- Human-AI/Robot Interaction/Collaboration & Human-Centered AI
- Multi-Agent Systems (e.g., Coordination, Learning, Planning, Swarm Intelligence)
- Intelligent Transportation Systems & Autonomous Driving & Smart City