Data-Augmented Physiological Modeling

  • Data assimilation in modeling hemodynamic

  1. H. Gao*, X. Zhu, J.-X. Wang. A Bi-fidelity Surrogate Modeling Approach for Uncertainty Propagation in Three-Dimensional Hemodynamic Simulations. Computer Methods in Applied Mechanics and Engineering, 366, 113047, 2020. [Arxiv, DOI, bib]
  2. H. Gao*, J.-X. Wang, A Bi-fidelity Ensemble Kalman Method for PDE-Constrained Inverse Problems, Computational Mechanics, 67, 1115-1131, 2021 [Arxiv, DOI, bib]
  3. A. Arzani, J.-X. Wang, R. D’Souza, Uncovering near-wall blood flow from sparse data with physics-informed neural networks, Physics of Fluids, 33, 071905, 2021 (Featured Article) [Arxiv, DOI, bib]
  • Data-augmented modeling for intracranial dynamics


  1. J.-X. Wang, X. Hu, S. C. Shadden, Data-augmented modeling of intracranial pressure. Annals of biomedical Engineering, 2018 (Accepted) [Arxiv, DOI, bib].