I’m a PhD candidate in Computer Science at UC San Diego, where I am fortunate to be advised by Prof. Yian Ma, and closely collaborate with Prof. Tara Javidi, Prof. Sean Gao.

My primary research interests span reinforcement learning (RL), foundation models and Bayesian inference, with a focus on addressing fundamental challenges in sequential decision making under uncertainty. More recently, I am particularly interested in LLM alignment and reasoning, exploring how RL plays a role in these topics. The goal of my research is to design provably efficient and practical algorithms with performance guarantee, achieving both statistical and computational benefits.

During my PhD, I interned at IBM research, Amazon and Honda Research Institute, working on LLM for personlization, RL for ranking and recommendation systems, and robotics.

I have experience with fine-tuning LLMs and reward models, designing CoT prompting and reasoning frameworks, LLM decoding, and training R1-style reasoning LLMs using RL (e.g. PPO, GRPO).