## Shih-Hsin Wang

## About Me

I'm a third year PhD candidate in Mathematics at the University of Utah. My aim is to unveil profound truths, leveraging math's astonishing might to enrich the world's insights.

### As an Applied Mathematician, ...

I aim to understand the underlying principles behind the success of neural networks and reveal insights that can guide future developments and applications of deep learning. Currently, I am primarily concentrating on the domains of Geometric Deep Learning and Diffusion models.

### As a Pure Mathematician, ...

I am passionate about studying the theory of singularities in algebraic geometry, with a particular interest in exploring the space of arcs and addressing Nash problems.

### As a Mathematician, ...

I also participate in some projects in other fields that require mathematical analysis.## Publications

### Theoretical Machine Learning

**An Explicit Frame Construction for Normalizing 3D Point Clouds**

Baker, J.*, **Wang, S. H.***, de Fernex, T., Wang, B.,

The Forty-first International Conference on Machine Learning. 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.,

The Twelfth International Conference on Learning Representations. 2024

### Algebraic Geometry

**Families of jets of arc type and higher (co)dimensional Du Val singularities**

de Fernex, T., & **Wang, S. H.**

Comptes Rendus. MathÃ©matique 362.S1 (2024): 119-139.

### 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.

60th ACM/IEEE Design Automation Conference (DAC). IEEE, 2023