Department of Aerospace and Mechanical Engineering
Lucy Family Institute for Data & Society
University of Notre Dame
Areas of Expertise: Scientific Machine Learning, Data Assimilation, Bayesian Inference, CFD, Uncertainty Quantification, Optimization, Hemodynamics, Turbulence.
Dr. Jian-Xun Wang received his bachelor degree in Naval Architecture and Ocean Engineering from the Harbin Institute of Technology in 2011. He completed his master’s program in Mechanical Engineering in 2013 from the same university. He joined the graduate program in the Department of Aerospace and Ocean Engineering at Virginia Tech in 2013 and received a master degree in Ocean Engineering and a Ph.D. degree in Aerospace Engineering in 2016 and 2017, respectively. Subsequently, he conducted postdoctoral research at the University of California, Berkeley. He joined the College of Engineering as a tenure-track assistant professor at the University of Notre Dame in 2018.
Dr. Wang’s research focuses on data-driven/augmented computational modeling, which broadly revolves around physics-informed machine learning, Bayesian data assimilation, and uncertainty quantification. The main idea is to develop accurate physics-based computational models by leveraging available data from high-fidelity simulations, experiments, and clinical measurements using advanced data assimilation and machine learning techniques. Moreover, he is also interested in quantifying and reducing uncertainties associated with the computational models.