About Me
I am a Ph.D. student in Mathematics at 
Purdue University, advised by Prof. Guang Lin.
Previously, I received my master’s degree from 
Carnegie Mellon University, where I worked with Prof. Shixiang Woody Zhu.
Research Interests
My research focuses on generative models and scientific machine learning. I study diffusion models for language, images, and PDE data, with particular interests in model distillation and reward-based post-training.
I am also interested in uncertainty quantification, sampling methods, and learning dynamical systems from data.
News
- Sep 2026Phys-Instruct accepted to NeurIPS 2026. Paper
- 2026DiDi-Instruct accepted to ICLR 2026. Paper
- 2026BLADE published in Machine Learning: Science and Technology. Paper
- Aug 2025Passed my Ph.D. qualifying examinations at Purdue.
- Aug 2024Started my Ph.D. in Mathematics at Purdue, advised by Prof. Guang Lin.
Academic Service
Conference & workshop reviewer: ICML (2026); NeurIPS (2026); KDD AI4Sciences (2026); SIGKDD Time Series Workshop (2023, 2024).
Journal reviewer: JABES (2023); IEEE Transactions on Power Delivery (2024).