Wenrui Hao

Professor
Wenrui Hao.
Wenrui
Hao
He/Him/His
Professor
Department Affiliations
Interests
Scientific Computing
Machine Learning
Mathematical Biology
Address
Phone
814 865 3881
Website
https://sites.psu.edu/whao/

Research Interests

AI-driven digital twin modeling for biomedical applications, including Alzheimer’s disease and cardiovascular disease. Parameter estimation, identifiability analysis, and neural network discretization for nonlinear PDEs and nonlinear computation.

 

Selected Honors and Awards

  • Maximizing Investigators’ Research Award (MIRA), NIH (NIGMS)
  • Huck Leadership Fellowship, Penn State
  • Donald C. Rung Award for Distinguished Undergraduate Teaching

 

Selected Publications

Wang, S., & Hao, W. (2025). A systematic computational framework for practical identifiability analysis in mathematical models arising from biology. Advanced Science.

Hao, W., Lee, S., Xu, X., & Xu, Z. (2025). Stability and robustness of time-discretization schemes for the Allen–Cahn equation via bifurcation and perturbation analysis. Journal of Computational Physics, 521, 113565.

Hao, W., Lee, S., & Lee, Y. J. (2024). Companion-based multi-level finite element method for computing multiple solutions of nonlinear differential equations. Computers & Mathematics with Applications, 168, 162–173.

Hao, W., Liu, X., & Yang, Y. (2024). Newton-informed neural operator for computing multiple solutions of nonlinear partial differential equations. NeurIPS 2024.

Zheng, H., Huang, Y., Huang, Z., Hao, W., & Lin, G. (2024). HOMPINNs: Homotopy physics-informed neural networks for solving inverse problems of nonlinear differential equations with multiple solutions. Journal of Computational Physics, 112751.

Hao, W., Hong, Q., & Jin, X. (2024). Gauss–Newton method for solving variational problems of PDEs with neural network discretizations. Journal of Scientific Computing, 100(1), 17.

Hao, W., Lenhart, S., & Petrella, J. (2022). Optimal anti-amyloid-beta therapy for Alzheimer’s disease via a personalized mathematical model. PLOS Computational Biology, 18(9), e1010481.

Zheng, H., Petrella, J. R., Doraiswamy, P. M., Lin, G., & Hao, W. (2022). Data-driven causal model discovery and personalized prediction in Alzheimer’s disease. NPJ Digital Medicine, 5(1), 1–12.

Chen, Q., & Hao, W. (2019). A homotopy training algorithm for fully connected neural networks. Proceedings of the Royal Society A, 475(2231), 20190662.

Hao, W., & Harlim, J. (2018). An equation-by-equation method for solving the multidimensional moment-constrained maximum entropy problem. Communications in Applied Mathematics and Computational Science, 13(2), 189–214.

Wang, Y., Hao, W., & Lin, G. (2018). Two-level spectral methods for nonlinear elliptic equations with multiple solutions. SIAM Journal on Scientific Computing, 40(4), B1180–B1205.

Hao, W., Komar, H. M., Hart, P. A., Conwell, D. L., Lesinski, G. B., & Friedman, A. (2017). Mathematical model of chronic pancreatitis. Proceedings of the National Academy of Sciences, 114(19), 5011–5016.

Hao, W., & Friedman, A. (2016). Mathematical model on Alzheimer’s disease. BMC Systems Biology, 10(1), 1–18.

Hao, W., & Friedman, A. (2014). The LDL–HDL profile determines the risk of atheros