Shih-Hsin Wang
I’m a fourth-year PhD candidate in Mathematics at the University of Utah, currently visiting UCLA. My research bridges theory and application, spanning geometric deep learning, generative models (e.g., flow matching & diffusion models), and algebraic geometry. I'm especially passionate about AI for Science—leveraging deep mathematical insight to design practical, high-impact models for molecular and biological applications.
Open to research & data scientist roles in ML, Generative Modeling, and AI for Science (See full CV).
News & Updates
- May 2025 – Our paper "Improving Flow Matching by Aligning Flow Divergence" has been accepted to ICML 2025.
- Apr 2025 – ICLR 2025 Oral Presentation: Going to present our paper on molecular graph representation. [Slides] [Poster] [Code]
- Mar 2025 – Started visiting UCLA under Andrea Bertozzi, working on flow matching and its applications in RNA/DNA 3D folding.
Education
University of Utah, Salt Lake City, UT
Ph.D. Candidate in Mathematics
Advisors: Bao Wang, Tommaso de Fernex
Aug. 2021 – Anticipated May 2026
National Taiwan University, Taipei, Taiwan
Bachelor of Science in Mathematics
Sep. 2016 – Jun. 2020
Publications
Machine Learning
Improving Flow Matching by Aligning Flow Divergence
Wang, S. H.*, Huang, Y.*, Transue, T.*, Feldman, W. M., Zhang, H., Wang, B.
ICML 2025
E(3)-Equivariant Fragment-based Graph Neural Networks for Biomolecules
Wang, S. H., Huang, Y., Transue, T., Baker, J. M., Forstater, J., Strohmer, T., Wang, B.
Under Review
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
Wang, S. H.*, Huang, Y.*, Baker, J., Sun, Y. E., Tang, Q., Wang, B.
ICLR 2025 [Oral Presentation]
[Slides]
[Poster]
[Code]
Learning to Control the Smoothness of Graph Convolutional Network Features
Wang, S. H.*, Baker, J.*, Hauck, C. D., Wang, B.
Under Review
An Explicit Frame Construction for Normalizing 3D Point Clouds
Wang, S. H.*, Baker, J.*, de Fernex, T., Wang, B.
ICML 2024
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
Wang, S. H., Hsu, Y. C., Baker, J., Bertozzi, A. L., Xin, J., Wang, B.
ICLR 2024
Algebraic Geometry
Arcs on Du Val Singularities in Arbitrary Characteristics
Wang, S. H., de Fernex, T.
In Preparation
Families of Jets of Arc Type and Higher (Co)Dimensional Du Val Singularities
Wang, S. H., de Fernex, T.
C.R. Math. Acad. Sci. Paris, Special Volume in Memory of Jean-Pierre Demailly (2024)
Other Fields
GenFuzz: GPU-Accelerated Hardware Fuzzing Using Genetic Algorithm with Multiple Inputs
Lin, D. L., Zhang, Y., Ren, H., Khailany, B., Wang, S. H., Huang, T. W.
ACM/IEEE Design Automation Conference (DAC), 2023
Highlights (See full CV)
Recent Experience
- Visiting Graduate Researcher, UCLA (Mar 2025 – Present)
Initiating a pipeline for 3D RNA/DNA folding from secondary structure using flow-matching models, supervised by Andrea Bertozzi. - Research Intern, Los Alamos National Lab (May – Aug 2024)
Developed a sparse, rigid, and hyperparameter-free graph representation for molecular structures, supervised by Qi Tang.
Invited Talks & Presentations
- ICLR 2025 – Oral presentation on “A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules” (Singapore)
- JMM 2025 – “Expanding the Mathematical Horizons of Machine Learning”
- SIAM GL 2023 – “Leveraging Geometric Symmetries with GNNs”
- NCTS Algebraic Geometry Seminar 2023 – “Families of Jets on Du Val Singularities”
Academic Service
- Reviewer: ICLR 2025, ICML 2024–25, NeurIPS 2024–25, AISTATS 2025
- Journal Reviewer: TMLR, SIAM J. on Applied Algebra and Geometry, ACM TOSN