I am Jiawei Wang (王家伟). I am a tenure-track Assistant Professor in Intelligent Transportation at the Systems Hub, HKUST (Guangzhou) from May 2026. I worked as a Postdoctoral Researcher at the Graduate School of Interdisciplinary Information Studies, The University of Tokyo, and a Visiting Scholar at the Center for Spatial Information Science, The University of Tokyo, from Nov 2023.
I received my Ph.D. in Civil Engineering from McGill University, Canada. Before that, I obtained my B.Eng. in Transportation Engineering and M.Eng. in Traffic Information Engineering and Control from Sun Yat-sen University, China.
My research lies at the intersection of artificial intelligence and transportation systems, with a particular interest in building an integrated scientific route from traffic generation, to traffic understanding, and further to traffic control. I develop data-driven and behaviorally grounded methods for mobility generation, generative traffic simulation, and public transportation optimization.
My group is focusing on generative intelligent transportation (GIT). I am seeking 2–3 PhD students, for Spring 2027 and beyond, with a strong interest in AI/data-driven traffic understanding and control. If you're interested, please send me an email at jiaweiw[at]hkust-gz.edu.cn. Please include a CV, a research statement, and an academic transcript. Please use “PhD/RA Application + [Your name]” as your email subject.
Joining HKUST(GZ) as a tenure-track Assistant Professor in Intelligent Transportation.
Two papers accepted to ICLR 2026: ELLMob and TrajFlow.
Our paper on LLM agents for personal mobility generation was presented at NeurIPS 2024.
Large language models for human mobility generation, event-aware behavior modeling, and urban analysis.
NeurIPS 2024
Jiawei Wang, Renhe Jiang, Chuang Yang, Zengqing Wu, Shibasaki Ryosuke, Koshizuka Noboru, Xiao Chuan
Behaviorally grounded LLM agents for simulating personal mobility in cities.
ICLR 2026
Yusong Wang, Chuang Yang, Jiawei Wang, Xiaohang Xu, Jiayi Xu, Dongyuan Li, Chuan Xiao, Renhe Jiang
An event-aware self-aligned LLM framework for human mobility generation under dynamic urban contexts.
Generative AI methods for traffic simulation, trajectory synthesis, and transportation system modeling.
Learning-based control for bus operations, transit reliability, and coordinated mobility systems.
Transportation Research Part C 2020
Jiawei Wang, Lijun Sun
A multi-agent deep RL framework for adaptive bus holding control.
IJCAI 2021
Jiawei Wang, Lijun Sun
Asynchronous multi-agent reinforcement learning for robust bus bunching mitigation.
IEEE TITS 2022
Jiawei Wang, Lijun Sun
Distributional multi-agent RL for robust transit control under uncertainty.
Transportation Research Part C 2023
Jiawei Wang, Lijun Sun
Multi-objective RL for coordinated control in multi-line bus systems.
May 2026 – Future
HKUST (Guangzhou)
Building a research program on Generative Intelligent Transportation.
Nov, 2023 – Mar, 2026
Graduate School of Interdisciplinary Information Studies, The University of Tokyo
Research on mobility generation.
2023 – Present
Center for Spatial Information Science, The University of Tokyo
Research on urban mobility generation and understanding.
2019 – 2023
McGill University
Multi-agent deep reinforcement learning for public transport vehicle fleet control
2016 – 2019
Sun Yat-sen University
Large-scale urban traffic state prediction based on deep learning.
2012 – 2016
Sun Yat-sen University
Foundations in transportation engineering and systems analysis.