About this Event
33 Oxford Street, Cambridge, MA 02138
Widely Applied Mathematics presents...
"Rare and Extreme Events in PDE Systems Involving Random Parameters"
Professor Georg Stadler, New York University's Courant Institute of Mathematical Sciences
Thursday, October 24
2:00 - 3:00pm
Maxwell Dworkin G115
Abstract: Estimation of tail probabilities in systems that involve uncertain parameters or white noise forcing is important when these unlikely events have severe consequences. Examples of such events are hurricanes, energy grid blackouts or failure of engineered systems. After illustrating the challenges of estimating rare event probabilities, I will show a connection between extreme event probability estimation and PDE-constrained optimization that is made precise by large deviation theory. The approach leads to practical methods to estimate small probabilities, and a novel class of challenging, large-scale constrained optimization problems. I will show examples governed by the shallow water and the Navier Stokes equations. Time permitting, I will also show recent results on Bayesian inference in large-scale geodynamics models and highlight some mathematical challenges in this estimation.
Short Bio: Georg Stadler is a professor of Mathematics and Computer Science at New York University's Courant Institute of Mathematical Sciences. His research is in Bayesian inverse problems and uncertainty quantification, PDE-constrained optimization under uncertainty, parallel PDE solvers, and extreme event estimation. This research is often driven by real world applications, primarily in geoscience, climate, and plasma physics. Before joining the Courant Institute in 2014, he was a research scientist and postdoc at the Oden Institute, which is part of UT Austin. He obtained a PhD in Mathematics from the University of Graz (Austria) under supervision of Karl Kunisch. His research is supported by NSF, ONR, DOE and the Simons Foundation. He has obtained multiple research recognitions, including the Gordon Bell Award (2015), the Springer CSE prize (2011) and the SIAM CSE Best Paper Award (2019).