Published several papers including 'Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory' (In Submission), 'Statistical guarantees for lifelong reinforcement learning using pac-bayesian theory' (AISTATS 2025), 'Quantile Additive Trend Filtering' (AISTATS 2025), 'Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees' (AISTATS 2024), 'Reinforcement Learning Under a Multi-agent Predictive State Representation Model: Method and Theory' (ICLR2022 Spotlight), 'Integrating Independent and Centralized Multi-agent Reinforcement Learning for Traffic Signal Network Optimization' (AAMAS 2020 Extended Abstract), etc.
Research Experience
Involved in multiple research projects including deep learning models for the 3D binding affinity of proteins, Predictive Platform for Fast Antibiotic Susceptibility Test, Simulated Intelligent Robot Tracking Agent, etc.
Education
Ph.D. student in Statistics at UCLA, advisor information not provided.
Background
Ph.D. student in Statistics at UCLA. Research interests include: High-dimensional nonparametric statistics, Deep graph neural networks, Multi-agent reinforcement learning, Optimization with optimal control, Statistical inference for Epidemiology.
Miscellany
Personal interests and other information not provided.