Sean is the Managing Director of Michigan Traffic Lab, where he delegates a range of responsibilities. 

He also works as a Research Engineer in the Engineering Systems Group at the University of Michigan Transportation Research Institute (UMTRI). Sean holds an MS degree in Civil and Environmental Engineering from the University of Michigan, Ann Arbor, and an MS degree in Electrical Engineering from the University of Bristol, UK. He also earned a BS degree from Beijing University of Posts and Telecommunications, China.

Sean's research interests are primarily focused on cooperative driving automation and related applications that use roadside perception, edge-cloud computing, and V2X communications to accelerate the deployment of automated vehicles. He has extensive experience in implementation of large-scale deployments, such as the Safety Pilot Model Deployment (SPMD), Ann Arbor Connected Vehicle Testing Environment (AACVTE), and Smart Intersection Project. Moreover, he has been involved in many research projects funded by public agencies such as USDOT, USDOE, and companies such as Crash Avoidance Metric Partnership (CAMP), Ford Motor Company, GM Company, and Honda R&D Americas, among others.

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.

Depu Meng currently works as a postdoc at Michigan Traffic Lab. He received his Ph.D. degree in the Department of Automation from the University of Science and Technology of China, in 2023, and his B.E. in Electrical Engineering from University of Science and Technology of China in 2018. His research interests include computer vision, roadside sensing, and safety-critical event identification.

Ran Sun is currently a postdoc in Michigan Traffic Lab at the University of Michigan. He received a Ph.D. in Civil Engineering (Transportation) from the University of California, Davis, where he also holds an M.S. degree in Statistics. He holds a B.S. in Railway Transportation from Southwest Jiaotong University. His research focuses on the intersection among transportation network and flow modeling, graph-based machine learning and decision-making under uncertainties. He is also actively conducting research in connected and automated vehicles and smart transportation systems.