T3: Tensor Thinking for Transportation — A High-Dimensional, Low-Rank Approximation Framework for Data- and AI-Driven Systems Modeling
CME Department Seminar
October 9, 2025
11:00 AM - 12:00 PM America/Chicago
Presenter: Xuesong (Simon) Zhou, PhD, Arizona State University
Location: ERF Room 1047 or Zoom at https://uic.zoom.us/j/5357181241?pwd=VHQ5dE53eG5DWmREYXZ4ekRJQXZJUT09
Meeting ID: 535 718 1241
Passcode: Lin@842cme
Abstract: Transportation systems involve complex, multiway interactions across spatial, temporal, and modal dimensions that traditional matrix-based methods struggle to capture. We introduce Tensor Thinking for Transportation (T3), a unifying framework that represents transportation states as high-dimensional tensors while embedding physical constraints within low-rank decompositions. Through 10 illustrative examples—including origin–destination flows, vehicle trajectories, and operational control—we show that physics-informed tensor regression enables substantial dimensionality reduction without sacrificing interpretability of transportation phenomena. The framework aligns naturally with heterogeneous computing architectures, supporting continuous tensor operations on GPUs and discrete optimization on quantum processors. Overall, T3 establishes a unified mathematical foundation for transportation modeling that integrates artificial intelligence capabilities with domain-specific physical principles.
Speaker Bio: Xuesong (Simon) Zhou is a professor of transportation systems at Arizona State University (ASU). His research focuses on methodological advances in multimodal transportation planning, including dynamic traffic assignment, traffic estimation and prediction, large-scale routing, and rail scheduling.
Zhou has published many papers in leading journals (Transportation Research Part B, Part C, etc.), with an H-index of 65. He serves on the Editorial Board of Transportation Research Part B, and has chaired the INFORMS Rail Applications Section (2016, 2025). He currently chairs the TRB Committee on Transportation Network Analysis (AEP13).
Date posted
Sep 24, 2025
Date updated
Sep 24, 2025