About
Welcome! I am a postdoctoral researcher in the NSAPH group at Harvard University. My research focuses on efficient and transferable AI for structured data, particularly computational optimal transport and geometric data analysis. I am passionate about developing mathematical AI frameworks to address real-world challenges, including climate and health adaptation.
I obtained my Ph.D. in Computer Science from Vanderbilt University, where I had the privilege of being advised by Dr. Soheil Kolouri. Before that, I received an M.S. in Mathematics from Vanderbilt University in 2021 and a B.S. in Mathematics from Chongqing University in 2019.
I’d be more than happy to connect if you’re interested in my research or potential collaborations! The best way to reach me is by email.
News
- [05/27/2026] I have successfully defended my doctoral dissertation, Efficient Optimal Transport for Modern AI!
- [01/19/2026] Our paper “EMPEROR: Efficient Moment-Preserving Representation of Distributions” was accepted at ICASSP 2026!
- [12/10/2025] I am happy to announce that I have been awarded the Russell G. Hamilton Graduate Leadership Institute Dissertation Enhancement Grant at Vanderbilt!
- [11/07/2025] Our paper “Policy Search, Retrieval, and Composition via Task Similarity in Collaborative Agentic Systems” got accepted at AAAI 2026!
- [06/02/2025] The preprint “Constrained Sliced Wasserstein Embedding” is available on arxiv.
- [04/29/2025] Our paper “ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans” got accepted at ICML 2025!
- [02/11/2025] We had three papers accepted at ICLR 2025! Among them, the “Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data” was selected as Spotlight!