Ziyuan Pu, Ph.D., Professor
Department of Intelligent Transportation and Spatial Informatics, School of Transportation
Email: ziyuanpu@seu.edu.cn, ziyuan.pu@monash.edu
Ziyuan Pu currently is a professor at Southeast University (SEU), and an Adjunct Senior Research Fellow at Monash University. He received his M.S. and Ph.D. from University of Washington, and his B.S. degree from SEU, China. His previous research focus on Intelligent Transportation Systems (ITS), traffic sensing, Intelligent Vehicles (IV), and Smart Road Infrastructures. He serves as an Associate Editor of IEEE Transactions on Intelligent Transportation Systems, and a Handling Editor of Transportation Research Record. He serves as a member of CAV Impacts Committee and AI Committee of ASCE T&DI, and a member of Transportation Research Board (TRB) Standing Committee on Information Systems and Technology (AED30) and Standing Committee on Artificial Intelligence and Advanced Computing Applications (AED50).
Selected Award & Honors
(+ indicates the students under my supervision)
Best Student Paper Award (Junlan Chen+), 4th International Symposium on Freeway and Tollway operations. Paper Title: “A Generative Deep Learning Approach for Highway Crash Severity Modeling with Imbalanced Data.” 2023.
Outstanding Technical Paper Award, Institute of Transportation Engineers (ITE). Paper Title: “Multi-Modal Traffic Speed Monitoring: A Real-Time System Based on Passive Wi-Fi and Bluetooth Sensing Technology.” 2022.
Excellence in Research Award (Early Career Category), Monash University, School of Engineering. 2022.
Excellent Paper Award, World Transport Convention. Paper Title: “Traffic Transformer: Extracting Dynamic and Hierarchical Spatiotemporal Features with Transformer.” 2021.
Excellence in Highway Safety Data Research Award, FHWA. Paper Title: “Leveraging Machine Learning to Explore Non-Linearity between Vertical Curve Features and Crash Frequency on Highways.” 2020.
Selected Publications:
(* indicates corresponding author)
Li S, Pu Z*, Cui Z, Lee S, Guo X, Ngoduy D. “Inferring Heterogeneous Treatment Effects of Crashes on Highway Traffic: A Doubly Robust Causal Machine Learning Approach.” Transportation Research Part C: Emerging Technologies. Accepted 2024.
Zhuang Y, Pu Z*, Hu J, Wang Y. “Illumination and Temperature-Aware Multispectral Networks for Edge-Computing-Enabled Pedestrian Detection.”IEEE Transactions on Network Science and Engineering. 2021
Pu Z, Cui Z*, Tang J, Wang S, Wang Y. “Multi-Modal Traffic Speed Monitoring: A Real-Time System Based on Passive Wi-Fi and Bluetooth Sensing Technology.”IEEE Internet of Things Journal. 2021
Pu Z, Zhu M, Li W, Cui Z, Guo X, Wang Y*. “Monitoring Public Transit Ridership Flow by Passively Sensing Wi-Fi and Bluetooth Mobile Devices.”IEEE Internet of Things Journal 8.1 (2020):474-486.
Cui Z, Lin L, Pu Z*, Wang Y. “Graph Markov Network for Traffic Forecasting with Missing Data.” Transportation Research Part C: Emerging Technologies 117 (2020): 102671.
Selected Research Projects:
PI. National Science Foundation of China, Excellent Youth Funds (Oversea). “Traffic Sensing and Big Data Analytics.” (Funding Period: 2023-2026)
PI. Key Laboratory of Transport Industry of Comprehensive Transportation Theory of Ministry of Transport, “The Theory and Practice of Traffic-Energy-Information-Infrastructure Multi-Network Cooperative Optimizations.” (Funding Period: 2023-2024)
PI. Monash University School of Engineering Seed Grant. “Identifying Spatial Causal Factors of Urban Traffic Congestions Based on Passive Wi-Fi Sensing Technology.” (Funding Period: 2021-2022)
Co-PI. United States Department of Transportation, Tier 1 University Transportation Center (CSET) Research Project. “Cost-Effective System for Rural Roadway Traffic, Surface Conditions and Weather Conditions Monitoring.” (Funding Period:2021-2022)
Co-PI. United States Department of Transportation, Tier 1 University Transportation Center (CSET) Research Project. “Developing Data-Driven Pedestrian Safety Assessment Methods for RITI Communities.” (Funding Period: 2020-2022)