About

Biography

Xingmin Wang is a ZJU100 Young Professor (Tenure-Track Assistant Professor) at the Institute of Intelligent Transportation, College of Civil Engineering and Architecture, Zhejiang University, and a selectee of the National Young Talent Program. He received his B.E. in Automotive Engineering from Tsinghua University in 2018 and his Ph.D. in Civil Engineering and Scientific Computing from the University of Michigan in 2023 under the supervision of Prof. Henry X. Liu. He then worked as a postdoctoral researcher and assistant research scientist at Michigan before joining Zhejiang University in August 2026.

His research draws on artificial intelligence, operations research and optimization, and data science to study traffic-flow modeling and simulation, transportation-network operations, and traffic control, with applications to connected vehicles, automated driving, transportation foundation models, and the low-altitude economy.

His work has appeared in Nature Communications, Transportation Research Part C, and European Journal of Operational Research. A representative line of work uses trajectories from a small share of connected vehicles to observe traffic conditions and optimize signal timing. The technology has been deployed at more than 1,400 intersections in Michigan, patented in the United States, and licensed to General Motors.

He co-taught the graduate course CEE 551 Traffic Science at the University of Michigan in Fall 2022, 2023, and 2024, covering traffic-flow theory, signal control, traffic simulation, and connected and automated transportation. In 2023, the course received a rating of 4.6/5.0 and his instructor rating was 4.9/5.0. He has also mentored undergraduate and master's students from the University of Michigan and Tsinghua University in traffic modeling, data analysis, and algorithm development.

Course materials from the former website remain available as a historical archive: CEE 551 Traffic Science ↗ · CEE 450 Introduction to Transportation Engineering ↗