Hi! I’m Zhihang Xu (徐之航), a Post-doc working at University of Houston, mentored by Prof. Min Wang.

📝 Publications

An adaptive Gaussian process method for multi-modal Bayesian inverse problems Z. Xu, X. Zhu, D. Li and Q. Liao.
Domain-decomposed Bayesian inversion based on local Karhunen-Loève expansions Z.Xu, Q. Liao, and J. Li. Journal of Computational Physics, vol. 504, p. 112856, 2024
A domain-decomposed VAE method for Bayesian inverse problems Z. Xu, Y. Xia, and Q. Liao. International journal for uncertainty quantification, vol. 14, no. 3, p. 67-95, 2024
Deep neural network based adaptive learning for switched systems J.He, Z. Xu, and Q.Liao. Discrete and Continuous Dynamical Systems, Series S. vol. 16, no. 7, p. 1827-1855, 2023
Gaussian process based expected information gain computation for Bayesian optimal design Z.Xu, and Q. Liao. Entropy, vol. 22, no. 2, p. 258, 2020
More asymptotic expansions for the Barnes $G$-function Z.Xu, and W. Wang. Journal of Number Theory , vol. 174, pp. 505–517, 2017

In preparation

Weak TransNet: A Petrov-Galerkin based neural network method for solving elliptic PDEs, Z.Xu, M. Wang, and Z. Wang
Parametrization of subgrid scales in long-term simulations of the shallow-water equations using machine learning and convex limiting, A. Mojamder, Z.Xu, M. Wang, and I. Timofeyev

2025 Travel Supprot, 2025 Research Collaboration Workshop in Science of Data and Mathematics (WiSDM) on Diffusion Generative Models for Inverse Problems in Imaging
2025 Travel Support, AWM (Association for Women in Mathematics), AWM Research Symposium
2025 Travel Support, ICERM (Institute for Computational and Experimental Research in Mathematics), Computational Learning for Model Reduction Workshop
2017-2022 Academic scholarship of ShanghaiTech University
2021 Outstanding TA of ShanghaiTech University
2017 Excellent graduate of Zhejiang Sci-Tech University
2016 Meritorious Winner of Mathematical Contest In Modeling
2013-2017 Scholarship of Zhejiang Sci-Tech University
Teaching
Instructor @ UH, Discrete mathematics (undergraduate), Fall 2024
TA @ SHTU, Matrix computations (graduate), Fall 2020
TA @ SHTU, Computational science and engineering (undergraduate), Fall 2019
TA @ SHTU, Machine Learning (graduate), Spring 2019

2017-2023, ShanghaiTech University, Ph.D. in Computer Science, supervised by Prof. Qifeng Liao.
2013-2013, Zhejiang Sci-Tech University, B.S. in Applied Mathematics

“Weak TransNet: a Petrov-Galerkin based method for partial differential equations”, session talk at the 2025 AWM Research Symposium, Madison, Wisconsin, May 2025
“Weak TransNet: a Petrov-Galerkin based method for partial differential equations”, RTG NASC Ranch Retreat at Rice University, Houston, Texas, May 2025
“Weak TransNet: a Petrov-Galerkin based method for partial differential equations”, seminar talk at University of Houston, Houston, Texas, April 2025
“Domain-decomposed methods for Bayesian inverse problems”, poster presentation, Workshop on Computational Learning for Model Reduction, Providence, Rhode Island, Jan 2025
“Domain-decomposed methods for Bayesian inverse problems”, poster presentation, SIAM TX-LA Section, Waco, Texas, October 2024
“Gaussian process based Bayesian optimal experimental design”, contributed talk at CSIAM, online, China, October 2022
“Gaussian process based Bayesian optimal experimental design”, invited talk of uncertainty quantification symposium at CSIAM, Hefei, China, September 2021
“Gaussian process based Bayesian optimal experimental design”, invited talk at CSIAM-UQ, Changsha, China, May 2021