About

I am a Ph.D. student in Computer Science at UCLA, fortunate to be advised by Prof. Quanquan Gu. My research is on machine learning theory, including reinforcement learning, bandits, large language models, and diffusion models. I am a 2025 Amazon Fellow.

I received a B.Sc. in Pure and Applied Mathematics from Tsinghua University in 2022 and an M.S. in Computer Science from UCLA in 2024. I interned at Microsoft Research Asia – Vancouver in summer 2024 and at ByteDance in summer 2026.

[I am on the 2026–2027 job market.] Please feel free to contact me about positions in academia or industry.

Research interests

• Reinforcement learning: Markov decision processes, bandits, and agents
• Large language models: RLHF, robustness to adversarial feedback, and test-time compute
• Diffusion models: fast ODE/SDE solvers, convergence analysis, and log-concave sampling

Recent news

• Jul 2026ICML 2026 Gold Reviewer.
• Jul 2026Three papers at ICML 2026 and one paper at the ICML 2026 DEMO Workshop.
• Apr 2026Joined the development of EurekaClaw.
• Jan 2026One paper about inference-time scaling is accepted at ICLR, 2026.
• 2025Amazon Fellow.

A proud fact

I received top reviewer awards at ICML, ICLR, and NeurIPS.