Tianming Liu's Homepage

1233 G.G.Brown Laboratory
University of Michigan
Ann Arbor, MI 48105
I am a Ph.D. student advised by Dr. Yafeng Yin in the Civil and Enviornmental Enginnering Department at University of Michigan, majoring in transportation systems engineering. I am expected to obtain a Ph.D. degree in transportation engineering in Fall 2025, and have obtained my B.S. degree in control science and engineering from Tsinghua University in 2020.
My research operates at the intersection of behavioral science, artificial intelligence, and network theory to craft next-generation models and management strategies for intelligent transportation systems. Methodologically, my research integrates behavior economics, statistical learning, network modeling, queueing theory, and generative artificial intelligence. Currently, my research work features:
- Agentic-LLM-powered models and simulations of transportation systems
- Multimodal data fusion and high-fieldity behavior modeling
- Behavior-informed operations management of mobility systems
I am currently on the academic job market for the 2025-2026 school year and is seeking a tenure-track assistant professor position related to transportation engineering, systems engineering and urban artificial intelligence.
news
Aug 21, 2025 | I give a talk at MIT LIDs on my agentic-LLM-based travel demand modeling research. |
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selected publications
- arXivAligning LLM with human travel choices: a persona-based embedding learning approacharXiv preprint arXiv:2505.19003, 2025
- AAAI workshopLlm-abm for transportation: Assessing the potential of llm agents in system analysisAccepted to AAAI workshop "AI for Urban Planning", 2025
- AI4TToward llm-agent-based modeling of transportation systems: A conceptual frameworkArtificial Intelligence for Transportation, 2025
- TRBCan large language models capture human travel behavior? evidence and insights on mode choiceAvailable at SSRN 4937575, Accepted by the 104th TRB Annual Meeting, 2024
- TRCThreshold-based incentives for ride-sourcing drivers: Implications on supply management and welfare effectsTransportation Research Part C: Emerging Technologies, 2023
- TRCEffects of threshold-based incentives on drivers’ labor supply behaviorTransportation Research Part C: Emerging Technologies, 2023