Faculty and Staff
Henry Liu, Ph.D.
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.
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.
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'.
Tinghan Wang received his Ph.D. and B.S. in Mechanical Engineering from Tsinghua University, Beijing, in 2022 and 2016, respectively. His research interests include automated vehicle evaluation, decision-making, end-to-end self-driving and multi-objective reinforcement learning.
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.
Xingmin Wang currently works as a postdoc at Michigan Traffic Lab. He received his Ph.D. degree in Civil Engineering and Scientific Computing from the University of Michigan, Ann Arbor, in 2023, and his B.E. in Automotive Engineering from Tsinghua University in 2018. His research interests include traffic operations with automated and connected vehicles, traffic flow models, and transportation 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.
Yukun Zuo received his Ph.D. in Information and Communication Engineering from the University of Science and Technology of China, Hefei, in 2023. He previously earned his B.S. in Information Security from the same university in 2018. His research interests include cooperative driving automation, robust roadside perception, domain adaptation, and continual learning.
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.
Jiawei Wang currently works as a postdoc at Michigan Traffic Lab. He received his Ph.D. degree in Mechanical Engineering from Tsinghua University in 2023, and his B.E. degree in Automotive Engineering from Tsinghua University in 2018. During his Ph.D. research, he was also a visiting Ph.D. student with the Automatic Control Laboratory at École Polytechnique Fédérale de Lausanne (EPFL) from 2021 to 2022. His research interests include connected automated vehicles, traffic control, distributed control, and data-driven control.