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Ziyue Li is a W2 Professor of Transportation Analytics at the Technical University of Munich. His research focuses on spatiotemporal machine learning, data mining, smart cities, and smart mobility, aiming to enhance sustainability, efficiency, cost-effectiveness, and interpretability in transportation systems. He addresses complex spatiotemporal systems through perception, decision-making, and explanation, combining statistical data mining with deep learning and domain knowledge to design models that adapt to the realities of transportation systems. Li earned his Ph.D. from the Hong Kong University of Science and Technology, co-supervised by Arizona State University. He has served as a W1 Professor at the University of Cologne and as a Data Mining Researcher in the Hong Kong Science Park, among other industry roles. His research has been recognized with multiple awards, including the Paper Award at the IISE Annual Meeting and the Peter Luh Young Researcher Award from the IEEE Robotics Automation Society. He has contributed to leading conferences such as AAAI and ACM SIGKDD.
Technical University of Munich • Munich, Germany
Leading research in Transportation Analytics.
University of Cologne • Cologne, Germany
Part of the faculty focusing on advanced analytics in transportation.
Hong Kong Science Park • Hong Kong
Conducted research within the data mining domain.
Hong Kong MTR • Hong Kong
Oversaw research initiatives in transportation innovation.
Nokia Bell Labs • Hong Kong
Supported advanced research projects in data communications.