Reinforcement learning for multimodal routing
Learning coordinated route recommendations across multimodal transit networks, with attention to traveler preferences and system performance.
About me
I am a Ph.D. student in Civil Engineering at The University of Hong Kong.
My research focuses on data-driven modeling and decision-making for intelligent transportation systems. I develop reinforcement learning methods for multimodal route recommendation, LLM-enhanced probabilistic frameworks for few-shot travel data generation, and learning-based models for travel behavior and mobility simulation.
Research interests
LLM-enhanced travel data generation
Combining large language models and probabilistic modeling to generate travel survey data when only a small number of observations are available.
Travel behavior and traffic simulation
Modeling travel choices and mobility services through data-driven methods and multimodal simulation to support transportation planning and operations.
Background
My academic background spans automation, computer science, and civil engineering. I have held research assistant positions at The University of Hong Kong and The Chinese University of Hong Kong.
Education, teaching & experience