Yahong Yang
yyang66@binghamton.eduBiography
Yahong Yang received a PhD in mathematics from the Hong Kong University of Science and Technology in 2023. Yang was a postdoctoral scholar at Penn State University from 2023 to 2025 and a visiting assistant professor at the Georgia Institute of Technology from 2025 to 2026.
Yang鈥檚 research focuses on the mathematical foundations of deep learning for partial differential equations, including neural network approximation, statistical learning theory, and operator learning. Yang also develops mathematical models and computational methods for applications in materials science and biology.
Publications
- Wenrui Hao, Rui Peng Li, Yuanzhe Xi, Tianshi Xu, and Yahong Yang. 鈥淢ultiscale Neural Networks for Approximating Green鈥檚 Functions.鈥 SIAM Journal on Scientific Computing, 2026.
- Yahong Yang, Haizhao Yang, and Yang Xiang. 鈥淣early optimal VC-dimension and pseudo-dimension bounds for deep neural network derivatives.鈥 Advances in Neural Information Processing Systems (NeurIPS), 2023.
- Chuqi Chen, Yahong Yang, Yang Xiang, and Wenrui Hao. 鈥淎utomatic differentiation is essential in training neural networks for solving differential equations.鈥 Journal of Scientific Computing, 2025.
- Wenrui Hao, Xinliang Liu, and Yahong Yang. 鈥淣ewton informed neural operator for solving nonlinear partial differential equations.鈥 Advances in Neural Information Processing Systems (NeurIPS), 2024.
- Chuqi Chen, Yahong Yang, Yang Xiang, and Wenrui Hao. 鈥淟earn singularly perturbed solutions via homotopy dynamics.鈥 International Conference on Machine Learning (ICML), 2025.
Education
- PhD in mathematics, the Hong Kong University of Science and Technology, 2023
Research Interests
- Deep learning methods for solving partial differential equations
- Approximation and statistical learning theory of neural networks
- Neural operators and efficient training methods
- Mathematical modeling and simulation in materials science and biology