About¶
I am a Ph.D. student in the Department of Mathematics at the National University of Singapore (NUS), supervised by Prof. Zhenning Cai. I received my B.S. in Mathematics and Applied Mathematics from Zhejiang University in 2026.
My research lies at the intersection of numerical analysis, scientific computing, and scientific machine learning, with a particular focus on partial differential equations. I am especially interested in developing structure-preserving operator learning methods that incorporate mathematical and physical properties—such as conservation, positivity, entropy dissipation, and geometric structure—into data-driven models.
More broadly, I am interested in combining ideas from classical numerical methods with modern machine learning to build reliable and efficient solvers for challenging problems, particularly kinetic equations and conservation laws.
News¶
- 2026.08 — Started my Ph.D. studies in Mathematics at the National University of Singapore.
- 2026.07 — Graduated from Zhejiang University with a B.S. in Mathematics and Applied Mathematics.
- 2026.06 — Our paper Learning missing physics from legacy simulators with alternating neural integrators was published in Nature Communications. DOI
- 2026.06 — Our preprint LGNO: A Local-Global Neural Operator for Hyperbolic Conservation Laws became available on arXiv. arXiv
- 2025.10 — Received the Chu Kochen Scholarship, the highest honor bestowed upon Zhejiang University students.
Education¶
National University of Singapore (NUS)
Ph.D. student in Mathematics, 2026.08-
Zhejiang University
B.S. in Mathematics and Applied Mathematics, 2022.09-2026.07
Research Interests¶
- Structure-Preserving Operator Learning
- Scientific Machine Learning (SciML)
- Numerical Analysis for PDEs