Professorial Faculty
Technical University of Munich

Prof. Dr. Ziyue Li

Professorship

Transportation Analytics

School

TUM School of Management

Contact Details

Business card at TUMonline

Academic Career and Research Areas

Prof. Ziyue Li’s field of research is spatiotemporal machine learning and data mining for smart cities and smart mobility, aiming to enhance sustainability, efficiency, cost-effectiveness, and interpretability. His work addresses Perception, Decision, and Explanation in complex spatiotemporal systems. His research combines statistical data mining, deep learning, and domain knowledge to design models that adapt to the physical realities of transportation systems, with the ability to generalize to new tasks and datasets.

Prof. Li exels in both academic and industry expertise. He is W2 Professor TUM since 2025 as Professorship of Transportation Analytics. He earned his Ph.D. at Hong Kong University of Science and Technology, with co-supervision at Arizona State University in 2021. He served as W1 Professor at the University of Cologne (2022–2025) and Guest lecture at GaTech (2023). His industry roles include Data Mining Researcher at Hong Kong Science Park (2021–22), Research Manager at Hong Kong MTR (2020–21), and Research Intern at Nokia Bell Labs (2019–20).

Awards

  • Best Paper Award, QCRE, IISE Annual Meeting (2025)
  • Peter Luh Young Researcher Award (Runner-up), IEEE Robotics and Automation Society (2023)
  • Best Applied Paper Award (Finalist), INFORMS DMDA (2021)
  • Best Theoretical Paper Award (Finalist), INFORMS DMDA (2021)
  • Best Conference Paper Award, IEEE CASE Conference (2020)

Key Publications (all publications)

C. Liu, Q. Xu, H. Miao, S. Yang, L. Zhang, C. Long, Z. Li*, R. Zhao, “TimeCMA: Towards LLM-Empowered Time Series Forecasting via Cross-Modality Alignment”, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025).

Abstract

H. Jiang, Z. Li*, X. Xiong, J. Ruan, J. Lu, H. Mao, R. Zhao, “X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner”, The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024).

Abstract

T. Lan, Z. Li*,Z. Li, L. Bai, M. Li, F. Tsung, W. Ketter, R. Zhao, and C. Zhang. “MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis”. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023).

Abstract

Z. Mao, Z. Li*, D. Li, L. Bai, & R. Zhao. “Jointly Contrastive Representation Learning on Road Network and Trajectory”. The 31st ACM International Conference on Information & Knowledge Management (CIKM 2022).

Abstract

Z. Li*, N. D. Sergin, H. Yan, C. Zhang, and F. Tsung∗, “Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction”, AAAI Conference on Artificial Intelligence (AAAI 2020).

Abstract

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