Hello! I am a senior undergraduate at Sun Yat-sen University, majoring in Information and Computing Science. I am currently a visiting student in the Department of Statistics at the University of Wisconsin-Madison.

Research: My research aims to advance machine learning by developing principled, efficient, and reliable methods for scientific discovery and intelligent decision-making.

Currently, I am working on:

• Developing principled and efficient generative models, grounded in statistical theory, for both foundational understanding and application.
• Applying these models within AI for Science for complex scientific simulation tasks.
• Understanding and evaluating LLM agents through the lens of in-context learning and sequential decision-making under uncertainty.

At SYSU, I am fortunate to be advised by Prof. Pengxu Wei and Prof. Liang Lin.

At UW–Madison, I am fortunate to be mentored by Prof. Yiqiao Zhong.

I am also grateful to have the opportunity to work with wonderful advisors and mentors, including Prof. Hongseok Namkoong (Columbia Business School) and Prof. Jianxun Wang (Cornell University).

I am actively seeking Ph.D. opportunities for Fall 2026. Please feel free to contact me!

Recent News

• Nov. 2025. Released the preprint and project page for BELA. Check out the arXiv and the Leaderboard!

• Sep. 2025. Our paper introducing BELA (Benchmarking In-context Experiential Learning Through Repeated Product Recommendations) is under review at ICLR 2026.

• Aug. 2025. Successfully completed the iSURE Program at the University of Notre Dame.

• Jan. 2025. Developed a new theoretical framework, MVU-AE: Minimum Variance Unsupervised Autoencoder.

• Oct. 2024. Awarded National Scholarship of China.