Overview
My research centers on integrating emerging reinforcement learning technologies into intelligent transportation systems, with a particular focus on enhancing traffic safety through advanced adaptive traffic signal control.
Research Areas
Reinforcement Learning for Traffic Safety
Developing RL-based methods for traffic signal control that explicitly account for collision risk and safety constraints, moving beyond throughput-only optimization toward collision-free intersection management.
Applied AI in Finance
Exploring reinforcement learning frameworks for portfolio management and financial prediction, including margin trading strategies and risk-aware generative models for stock analysis.
Large Language Models & Robotics
Investigating the applications of large language models in embodied AI and robotic systems, exploring how language understanding can improve task planning and human-robot interaction.
Current Projects
- PairUpLight — Multi-agent RL for coordinated multi-intersection traffic signal control
- RAGIC — Risk-aware generative framework for stock interval construction
- SafeLight — RL method toward collision-free traffic signal control
For a complete list of publications, visit the Publications page or my Google Scholar profile.