Weizi Li

Weizi Li is an Assistant Professor of Computer Science in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He is also a member of the Institute for Future Mobility and directs the Fluidic City Lab. His research focuses on leveraging multi-agent simulation and reinforcement learning to design cyber-physical infrastructure for urban environments, particularly in autonomous systems and urban mobility. Li holds a PhD in Computer Science from the University of North Carolina at Chapel Hill and completed a postdoctoral fellowship at MIT.

Education: PhD in Computer Science from UNC Chapel Hill (advisor: Ming C. Lin), with prior affiliations at Disney Research, Lenovo Research, and others.

Research Interests: Li explores topics such as mixed traffic control, autonomous vehicle coordination, energy-efficient path planning for eVTOLs, and privacy-preserving traffic management. His work combines machine learning, robotics, and transportation engineering to address urban challenges. Recent projects are supported by the NSF, U.S. Department of Transportation, and NVIDIA.

Lab and Teams: The Fluidic City Lab develops solutions for fluidic urban systems, with a focus on adaptive traffic control and smart infrastructure. Collaborations span academia and industry.