Yanbing Wang, Ph.D.
I leverage large-scale data, advanced computation, and control technologies to address operational challenges in transportation systems. In my current role at Arizona State University as an assistant professor, I lead applied research initiatives in governments and industry partners on intelligent systems and mobility analytics. Prior to ASU, I was a postdoctoral researcher at Argonne National Laboratory, following my Ph.D. from the Institute for Software Integrated Systems at Vanderbilt University.
I am a five-time recipient of the Dwight D. Eisenhower Transportation Fellowship from the Federal Highway Administration and was named a Cyber-Physical Systems Rising Star by the National Science Foundation. My experience spans both academia and industries, including positions at Toyota Infotech Labs, Mitsubishi Electric Research Laboratories, and UCLA's Institute for Pure & Applied Mathematics.
My research is rooted in use-inspired philosophy: bridging theory and practice through real-world experimentation and close collaboration with public agencies.
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Hosting MAG’s Data & Analytics Group at ASU
May 06, 2025
Welcome Texas Transportation Institute to ASU
Mar 25, 2025
Reflections on TRB 2025
Jan 15, 2025
Projects
A digital twin infrastructure calibrated on real-world corridor data
Imagine you’re driving on a congested freeway and find yourself caught in stop-and-go waves. These seemingly spontaneous traffic patterns—where vehicles repeatedly speed up and slow down—are surpri...
Jul 01, 2024
I-24 MOTION: A new instrument for traffic science
The Tennessee Department of Transportation’s I-24 Mobility Technology Interstate Observation Network (MOTION) is a four-mile section of I-24 in the Nashville-Davidson County Metropolitan area with ...
Nov 12, 2023
Real-time multi-object tracking on streaming data: a graph algorithm that actualy scales
Multi-object tracking (MOT) is a well-established problem in computer vision. However, the emerging challenge for modern traffic management lies in scaling these algorithms to operate in real-time....
Sep 12, 2023
Customized adaptive cruise control eases phantom jams: a massive field experiment
This Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) project aims to reduce instabilities in traffic flow, called “phantom jams,” that cause congestion and wa...
Nov 22, 2022
Rectify vehicle trajectory data from video tracking algorithms
Vehicle trajectory data has received increasing research attention over the past decades. With the technological sensing improvements such as high-resolution video cameras, in-vehicle radars and li...
Aug 05, 2022
Personalized ACC in a digital twin framework
Advanced driver-assistance systems (ADAS) have matured over the past few decades with the dedication to enhance user experience and gain a wider market penetration. However, personalization compone...
May 11, 2021