Da Long
Ph.D. Student in Computer Science
Kahlert School of Computing, the University of Utah
About Me
I am a Ph.D. student in computer science at the Kahlert School of Computing, University of Utah. I earned my Bachelor of Science degree from the University of Arizona, with double majors in computer science and mathematics.
My research primarily focuses on AI for Science. This inlcudes long-term forecasting multi-scale and multi-physics dynamics, developing generative/determinstic neural operators for functional mapping, scientific large language model, foundation model for physics, etc. I am advised by Dr. Shandian Zhe.
My research interest includes:
- AI for Science: Foundation Model for Physics, Spatio-temporal Forecasting, Surrogate Modeling
- Probabilistic Learning: Scientific Large Language Model, Diffusion Model for Operator Learning, Gaussian Process
I am on job market for full-time roles starting in summer/fall 2026. Please feel free to reach out to me if you are hiring. Any opportunity is appreciated.
Publications
(2025).
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs.
ICML.
(2025).
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems.
AISTATS.
(2024).
A kernel approach for pde discovery and operator learning.
Physica D: Nonlinear Phenomena.
Preprint
(2024).
Pseudo Physics-Informed Neural Operators.
Preprint.
Teaching
Teaching Mentorships
- CS 6190 Probabilistic Machine Learning (Spring 2023)
- CS 6350 Machine Learning (Fall 2022)