Research

Research Interests

My research interests lie in scientific and theoretical machine learning as well as approximation theory and applications. 

Current Research

At Brown, I work in the CRUNCH group on neural operators and am fortunate to be advised by Zhongqiang Zhang (WPI) and George Em Karniadakis (Brown University).

Previous Research

I studied Genome Wide Associative Studies (GWAS) of neurodegenerative diseases under Dr. Li-San Wang (University of Pennsylvania Wang Lab) in 2021.

Publications

1. B. Shih, A. Peyvan, Z. Zhang, and G. E. Karniadakis, Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity, Under review (2024) [arXiv]

Bachelor's Thesis

• B. Shih, Temporal Learning Capacity of Transformers in Non-Markovian Dynamical Systems, Senior Honors Thesis, Brown University (2024) [pdf, slides]

Talks

• Approximation Theory: An Overview - Classical & Modern Perspectives, Brown University (2024)