1. Best Paper Award (Winner), Institute of Industrial and Systems Engineers (IISE), Quality Control and Reliability Engineering (QCRE) (2025)
2. Peter Luh Young Researcher Award (Runner-up), IEEE Robotics and Automation Society (2023).
3. Best Paper Award (Runner-up), Institute of Industrial and Systems Engineers, Quality Control and Reliability Engineering (QCRE) (2023)
4. Best Student Paper Award (Finalist), Institute of Industrial and Systems Engineers, Quality Control and Reliability Engineering (QCRE) (2022)
5. Best Applied Paper Award (Finalist), INFORMS Data Mining and Decision Analytics (DMDA) Workshop (2021).
6. Best Theoretical Paper Award (Finalist), INFORMS Data Mining and Decision Analytics (DMDA) Workshop (2021).
7. Best Conference Paper Award (Winner), IEEE International Conference on Automation Science and Engineering (CASE) (2020)
8. Best Student Poster Award (Finalist), INFORMS Quality, Statistics, and Reliability (QSR) Section (2020).
9. Best Student Paper Award (Finalist), INFORMS Data Mining (2020).
10. Best Student Paper Award (Finalist), INFORMS Quality, Statistics, and Reliability (QSR) Section (2020).

• Guest Editor, IISE Transactions, Special Issue on “Advances in Reinforcement Learning for In- telligent Systems”

Academia:

2025.08-present: W2 Professor, Department of Operations & Technology and Heilbronn Data Science Center, Technical University of Munich, Germany

2022.03-2025.08: W1 Professor, Department of Information Systems, University of Cologne, Germany

2023.01: Guest Lecturer hosting by Prof. Jan Shi, School of Industrial and Systems Engineering, Georgia Institute of Technology, U.S.A

2019.02-2021.08: PhD Co-supervision under Prof. Hao Yan, School of Computing and Augmented Intelligence, Arizona State University, U.S.A

2017.08-2021.08: PhD Supervision under Prof Fugee Tsung, Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Hong Kong

Industry:

2021.08-2022.03: Data Mining Researcher at Smart Mobility Group, Hong Kong Science Park, Hong Kong

2020.09-2021.08: Research Project Manager: Hong Kong MTR & HKUST, Hong Kong

2019.09-2020.01: Research Intern: Nokia Bell Labs, Germany

Selected current research projects / Research Areas

Spatiotemporal Machine Learning 

Spatiotemporal Large Language Models and Spatial Time-Series

High-dimensional Data Analytics and Tensor Decomposition

Reinforcement Learning and Generalist Agent 

Causal Structure Learning for Smart Mobility

Large Language Model for Future Corporate and Industry Application

Key Publications
 

Spatiotemporal Machine Learning

[1] 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).

[2] Z. Li, Y. Nie, Z. Li*, L. Bai, Y. Lv, R. Zhao, “Non-Neighbors Also Matter to Spatiotemporal Kriging: A New Contrastive-Prototypical Learning”, The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024).

[3] L. Wang, L. Bai, Z. Li*, R. Zhao and F. Tsung, “Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping”, IEEE 19th International Conference on Automation Science and Engineering (IEEE CASE 2023).

Spatiotemporal LLM and Spatial Time-Series

[1] C. Liu, S. Yang, Q. Xu, Z. Li*, C. Long, Z. Li, R. Zhao, “Spatial-Temporal Large Language Model for Traffic Prediction”, The 25th IEEE International Conference on Mobile Data Management (IEEE MDM 2024).

[2] 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).

[3] C. Liu, S. Zhou, H. Miao, Q. Xu, C. Long, Z. Li*, R. Zhao, “Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation”, The IEEE 41st International Conference on Data Engineering (ICDE 2025).

[4] J. Ye, W. Zhang, Z. Li*, J. Li, M. Zhao, F. Tsung, “MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning”, The 34th International Joint Conference on Artificial Intelligence (IJCAI 2025).

High-dimensional Data Analytics and Tensor Decomposition

[1] 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).

[2] Z. Li*, H. Yan, C. Zhang and F. Tsung∗, “Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile” in IEEE 16th International Conference on Automation Science and Engineering (IEEE CASE 2020).

[3] Z. Li*, H. Yan, C. Zhang, L. Sun, W. Ketter, and F. Tsung. “Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering”. International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2023).

[4] D. Sergin Nurretin, J. Hu, Z. Li, C. Zhang, F. Tsung, H. Yan*. “Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling”, INFORMS Journal on Data Science (IJDS 2024).

Reinforcement Learning and Generalist Agent 

[1] 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).

[2] H. Jiang, Z. Li*, Z. Li, L. Bai, H. Mao, W. Ketter, R. Zhao, “A General Scenario-Agnostic Reinforcement Learning for Traffic Signal Control”, IEEE Transactions on Intelligent Transportation Systems (IEEE TITS 2024).

[3] J. Ruan, Z. Li*, H. Jiang, J. Lu, H. Mao, R. Zhao, “CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Multi-intersection Traffic Signal Control”, Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2024).

[4] J. Lu, J. Ruan, H. Jiang, Z. Li*, H. Mao and R. Zhao, “DuaLight: Enhancing Traffic Signal Control by Leveraging Scenario-Specific and Scenario-Shared Knowledge”, The 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024).

Causal Structure Learning for Smart Mobility

[1] 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).

[2] J. Lin, Z. Li*, Z. Li, L. Bai, R. Zhao and C. Zhang, “Dynamic Causal Graph Convolutional Network for Traffic Prediction”, 2023 IEEE 19th International Conference on Automation Science and Engineering (IEEE CASE 2023).

[3] J. S. Junker, R. Hu, Z. Li*, W. Ketter, “Data-Driven Optimization of EV Charging Station Placement Using Causal Discovery”, The IEEE 21st International Conference on Automation Science and Engineering (IEEE CASE 2025).

Large Language Model for Future Corporate and Industry Application

[1] J. Ruan, Y. Chen, B. Zhang, Z. Xu, T. Bao, G. Du, S. Shi, H. Mao*, Z. Li, X. Zeng, and R. Zhao. “TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage”. The 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

[2] Y. Kong, J. Ruan, Y. Chen, B. Zhang, T. Bao, S. Shi, G. Du, X. Hu, H. Mao*, Z. Li*, X. Zeng, R. Zhao, “TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems”, The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024).