About me
Iām a third year Ph.D. student in Applied Mathematics at Stony Brook University supervised by Professor Yi Liu.
Previously, I obtained a Bachelor of Science degree from Stony Brook University in both applied mathematicsš and pure mathematicsš.
Iām interested in Neural Operators, Generative Models, and AI for Science; Iām also broadly interested in Machine Learning, discrete math, graph theory, and many other topics in applied mathematics and computer science. š
The best way to contact me is through email: wenhan(dot)gao(at symbol)stonybrook(dot)edu š«
News
- September 2024: Co-first author on a paper, in collaboration with FSU, accepted by NeurIPS on symmetries for molecular GNN active learning!
- September 2024: First author on a paper accepted by TMLR on symmetries in neural operators!
- August 2024: Finished teaching AMS 326, Numerical Analysis. Congrats to all my students on a job well done! Syllabus;Lecture Notes
- August 2024: Mentored undergraduate student Xiang Liu (freshman in CS/AMS), who successfully completed a summer research project on neural operators for climate change through the SUNY SOAR program. Congrats!
- March 2024: Awarded the Excellence in Student Teaching Award from the AMS department at Stony Brook for Fall 2023!
- December 2023: Finished teaching the graduate course AMS 595, Fundamentals of Computing. Congrats to all my students on a job well done! Syllabus;Lecture Notes
- August 2023: Passed Ph.D. qualifying exam in AMS!
- February 2023: First author on a paper on active learning-based sampling for high-dimensional PDEs published in the Journal of Computational Physics.
First or Co-first Author Publications
* indicates equal contributors.
Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism
R.Subedi*, L.Wei, W.Gao*, S.Chakraborty, Y.Liu.
The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
Coordinate Transform Fourier Neural Operators for Symmetries in Physical Modelings
W.Gao, R.Xu, H.Wang, Y.Liu.
Transactions on Machine Learning Research (TMLR), 2024
Active Learning Based Sampling for High-Dimensional Nonlinear Partial Differential Equations
W.Gao, C.Wang.
Journal of Computational Physics (JCP), 2023
First or Co-first Author Preprints
- One paper on the resolution-invariance and discretization mismatch errors in neural operators; submitted to ICLR 25; W.Gao, R.Xu, Y.Deng, Y.Liu
- One paper addressing the misalignment between optimized masks and actual explanatory subgraphs in 3D GNNs; ubmitted to ICLR 25; X.Liu*, W.Gao*, Y.Liu
- One paper on designing enhanced kernels for localized effects and interactions in FNO; Preprint; W.Gao, J.Luo, R.Xu, Y.Liu