Faculty Profile

Photograph of Georg Stadler

Georg Stadler

Professor of Mathematics
Warren Weaver Hall, Office 929


Ph.D. (Dr.), Mathematics, University of Graz, Austria, 2004.
M.S. (Mag.), Mathematics, University of Graz, Austria, 2001.
M.S. (Mag.), Mathematics and Geometry Education, Graz University of Technology and University of Graz, Austria, 2001.

Research Interests

My research focuses on solvers for large-scale PDE systems, on uncertainty quantification, and scientific computing and scientific machine learning. In particular, I work on Bayesian inverse problems, extreme event probability estimation, PDE-constrained optimization and optimization under uncertainty.

Most of my research is driven by societally important applications in climate (sea and land ice, tsunamis), in plasma physics (fusion) and in computational earth science (mantle flow and plate tectonics).

Selected Publications

Y. Shih, G. Stadler and F. Wechsung, Robust multigrid techniques for augmented Lagrangian preconditioning of incompressible Stokes equations with extreme viscosity variations, SIAM Journal on Scientific Computing, (2022).
S. Tong, E. Vanden-Eijnden, G. Stadler, Extreme event probability estimation using PDE-constrained optimization and large deviation theory, with application to tsunamis, Communications in Applied Mathematics and Computational Science, 16(2), pp 181-225, (2021).
T. Isaac, N. Petra, G. Stadler and O. Ghattas: Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet, Journal of Computational Physics 296, pp. 348-368 (2015).

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