The Director of Michigan Traffic Lab, Prof. Henry Liu, is a Professor in the Department of Civil and Environmental Engineering and the Director of Mcity at the University of Michigan, Ann Arbor. He is also a Research Professor at the University of Michigan Transportation Research Institute and the Director for the Center for Connected and Automated Transportation (USDOT Region 5 University Transportation Center). From July 2017 to August 2019, he took a leave of absence from the University of Michigan and served as Chief Scientist on Smart Transportation for DiDi, one of the leading mobility service providers in the world. While he was with DiDi, he led and managed the Smart Transportation Business Unit. Prof. Liu received his Ph.D. degree in Civil and Environmental Engineering from the University of Wisconsin at Madison in 2000 and his Bachelor degree in Automotive Engineering from Tsinghua University (China) in 1993. Prof. Liu conducts interdisciplinary research at the interface of transportation engineering, automotive engineering, and artificial intelligence. Specifically, his scholarly interests concern traffic flow monitoring, modeling, and control, as well as testing and evaluation of connected and automated vehicles. Professor Liu has nurtured a new generation of scholars, and some of his PhD students and postdocs have joined first class universities such as Columbia University, Purdue University, RPI, etc. Prof. Liu is the managing editor of Journal of Intelligent Transportation Systems.  

Rusheng Zhang received the B.E. degree in micro electrical mechanical system and second B.E. degree in Applied Mathematics from Tsinghua University, Beijing, in 2013, and the M.S. degree in electrical and computer engineering from Carnegie Mellon University in 2015 and Ph.D. in 2019. His research areas include vehicular networks, intelligent transportation systems, wireless computer networks, artificial intelligence and intra vehicular sensor networks. 

Ronan Keane is a current postdoc in Civil and Environmental Engineering at University of Michigan. He holds a PhD in Systems Engineering from Cornell University and a MS in Applied Math from University of Washington. His research focuses on traffic flow theory, traffic signal optimization, mathematical modeling, and optimization. Within optimization, his interests lie in nonlinear optimization, stochastic optimization/gradient estimation, and machine learning. He is actively developing havsim (Human and Autonomous Vehicle SIMulation, calibration, and optimization), a software package for solving optimization and control problems involving traffic models. In 2020 he was a fellow at the Institute for Pure and Applied Mathematics (IPAM) as part of their program 'Mathematical Challenges and Opportunities for Autonomous Vehicles'. 

Boqi Li received his Ph.D. in Mechanical Engineering from the University of Michigan, Ann Arbor, in 2022. He also holds a B.S. in Mechanical Engineering from the University of Illinois Urbana– Champaign and a M.S. in Mechanical Engineering from Stanford University. His research focuses on the modeling and decision-making for multi-agent systems, particularly for the application of connected, cooperative, and automated mobility systems where the navigation and motion planning of connected and automated vehicles are involved. He is interested in human driver behavior prediction with machine learning, multi-agent reinforcement learning, and graph neural networks.