About me
Ph.D. in Applied Math from Stony Brook
GenAI, AI for Science
The best way to contact me is through email: wenhan(dot)gao(at symbol)stonybrook(dot)edu 📫
First or Corresponding Author Publications
* indicates equal contributors/co-first authors; ‡ indicates equal senior contributors/co-corresponding authors
Feedback to Reasoning: LLM-Assisted Molecular Optimization with Domain Feedback and Historical Reasoning
Wenhan Gao, Xiran Fan, Chin-Chia Michael Yeh, Jiarui Sun, Yuzhong Chen, Menghai Pan, Mahashweta Das, Yi Liu.
Findings of the Association for Computational Linguistics: ACL, 2026
RL-Guider: Leveraging Historical Decisions and Feedback for Drug Editing with Large Language Models
X.Liu*, Y.Ding*, J.Qu, Y.Zhang, W.Gao‡, Y.Liu‡.
Findings of the Association for Computational Linguistics: ACL, 2025
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation
J.Qu*, W.Gao*, J.Zhang, X.Liu, H.Wei, H.Ling, Y.Liu.
The Forty-second International Conference on Machine Learning (ICML), 2025
Dynamic Schwartz-Fourier Neural Operator for Enhanced Expressive Power
W.Gao, J.Luo, R.Xu, Y.Liu.
Transactions on Machine Learning Research (TMLR), 2025
Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators
W.Gao, R.Xu, Y.Deng, Y.Liu.
The Thirteenth International Conference on Learning Representations (ICLR), 2025
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 size-consistent diffusion models for 3D molecular generation; Submitted to ICML 2026; W.Gao, J.Qu, Y.Liu
- One paper that reveals neural operators can learn hidden physics from data; Submitted to ICML 2026; W.Gao*, J.Luo*, R.Xu, F.Wan, X.Liu, Y.Liu