Alexandre Tartakovsky

Professor Alexandre Tartakovsky is a faculty member at the University of Illinois at Urbana-Champaign's Department of Civil and Environmental Engineering. His primary research focuses on water resources engineering, subsurface flow and transport, and physics-informed machine learning. He holds a M.Sc. from Kazan State University (1994) and a Ph.D. from the University of Arizona (2002).

His research integrates computational mathematics with geosciences, emphasizing stochastic modeling, uncertainty quantification, and multiscale phenomena. Notable contributions include physics-informed neural networks for inverse problems and Bayesian data assimilation techniques. Tartakovsky has held roles at Pacific Northwest National Laboratory (2004–2019) and the University of South Florida (2013–2014).

Research Interests: Inference and parameter estimation, multiscale modeling, uncertainty quantification, physics-informed machine learning, pore-scale multiphase flow, and subsurface flow dynamics.

Recent Publications: Recent work includes advancements in machine learning for geophysical inversion, stochastic control of power grids, and Bayesian surrogate models for dynamic systems. His 2025 articles highlight applications in load frequency control and randomized neural networks for uncertainty quantification.

Awards: Recipient of the DOE Early Career Award (2008), Presidential Early Career Award (2008), and multiple fellowships. Active in SIAM and AGU professional societies.

Labs/Teams: Hydrosystems Lab at UIUC, collaborating on computational hydrology and subsurface processes. Research spans from theoretical models to applied geoscience challenges.