# Donald Estep (Simon Fraser University)

##### Date

Friday December 3, 20212:30 pm - 3:30 pm

##### Location

Online (via Zoom)## Math & Stats Department Colloquium

**Friday, December 3rd, 2021**

**Time:** 2:30 p.m. **Place:** Online (via Zoom)

**Speaker:** Donald Estep (Simon Fraser University)

**Title:** Formulation and solution of stochastic inverse problems for science and engineering models

**Abstract:** Determining information about the state of a complex physical system from observations of its behavior is a fundamental problem in scientific inference and engineering design. Often, this can be formulated as the stochastic inverse problem of determining probability structures on parameters for a physics model corresponding to a probability structure on the output of the model. We describe the formulation and solution of stochastic inverse problems. Our approach yields a computationally tractable problem while avoiding alterations of the model like regularization and ad hoc assumptions about the probability structures. We present several examples, including a high-dimensional application to determination of parameter fields in storm surge models. We describe several extensions and on-going research.

**Donald Estep** is the Scientific Director of CANSSI and Canada Research Chair in Computational Probability and Uncertainty Quantification (Tier 1) in the Department of Statistics and Actuarial Science at Simon Fraser University. His awards include Fellow of the Society for Industrial and Applied Mathematics, the Computational and Mathematical Methods in Sciences and Engineering (CMMSE) Prize, and the Chalmers Jubilee Professorship of Chalmers University of Technology. His research interests include uncertainty quantification for complex physics models, stochastic inverse problems, adaptive computation, and modeling of multiscale systems. His application interests include ecology, materials science, detection of black holes, modeling of fusion reaction, analysis of nuclear fuels, hurricane wave forecasting, flow in porous media, and electromagnetic scattering.