About me

Iā€™m 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 mathematicsšŸ“™ and pure mathematicsšŸ“•.

Iā€™m interested in Neural Operators, Generative Models, and AI for Science; Iā€™m also broadly interested in Machine Learning, discrete math, graph theory, and many other topics in applied mathematics and computer science. šŸ‘€

The best way to contact me is through email: wenhan(dot)gao(at symbol)stonybrook(dot)edu šŸ“«

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

Paper | Code | BibTeX

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

Paper | Code | BibTeX

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