Faculty and Staff

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.

Shuo Feng, Ph.D.

fshuo@umich.edu

Assistant Research Scientist, University of Michigan Transportation Research Institute

Dr. Feng joined UMTRI as an assistant research scientist in Sep, 2021. Before that, he worked as a postdoctoral research fellow in the Department of Civil Environmental Engineering at the University of Michigan. He received his Ph.D. degree and Bachelor’s degree in the Department of Automation from Tsinghua University, China, in 2014 and 2019. His current research interests include optimal control, automated driving system testing and evaluation, and transportation data analysis.

Shengyin(Sean) Shen

shengyin@umich.edu

Research Engineer, University of Michigan Transportation Research Institute

Sean is a Research Engineer in the Engineering Systems Group at the University of Michigan Transportation Research Institute (UMTRI). He earned his MS degree in Civil and Environmental Engineering from the University of Michigan, Ann Arbor, and in Electrical Engineering from the University of Bristol, UK. He also has a BS degree from Beijing University of Posts and Telecommunications, China. His research interests focus on traffic control, mobility and safety applications with connected and automated vehicles.

Rusheng Zhang, Ph.D.

rushengz@umich.edu

Postdoctoral Research Fellow, Department of Civil and Environmental Engineering

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.

Xiaowei(Tom) Shi, Ph.D.

tomcee@umich.edu

Postdoctoral Research Fellow, Department of Civil and Environmental Engineering

Dr. Shi is a Postdoctoral Research Fellow in the Department of Civil Environmental Engineering at the University of Michigan. He received his Bachelor’s and Master’s degrees in the School of Traffic and Transportation from Beijing Jiaotong University, China, in 2015 and 2018. He received his second Master’s degree and Ph.D. degree in the Department of Civil and Environmental Engineering from the University of South Florida in 2020 and 2021. His research aims to establish a set of methodologies to understand, predict and eventually improve future transportation systems via sensors, controllers, and design variables rendered by emerging technologies (e.g., connected, automated, modular, and electric vehicles).