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IQS^3 Colloquium: Formulation and Solution of Stochastic Inverse Problems for Science and Engineering Models

February 14, 2022 at 4:00 pm - 5:00 pm

Free

The IQS^3 Colloquium invites you to attend a talk by Donald Estep.

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.

This talk describes the formulation and solution of stochastic inverse problems. Their approach yields a computationally tractable problem while avoiding alterations of the model like regularization and ad hoc assumptions about the probability structures. They present several examples, including a high-dimensional application to determination of parameter fields in storm surge models. They describe several extensions and on-going research.

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About the Speaker

Donald EtsapDonald Estep is the Scientific Director of CANSSI and Canada Research Chair in Computational Probability and Uncertainty Quantification (Tier 1). He recently joined the Department of Statistics and Actuarial Science at Simon Fraser University, moving from Colorado State University, where he was Department Chair, University Distinguished Professor and University Interdisciplinary Research Scholar. 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.

Details

Date:
February 14, 2022
Time:
4:00 pm - 5:00 pm
Cost:
Free

Additional Info

Registration/RSVP Required
Yes (see event description)
Event Type
Talk/Lecture
Topic
Science, Technology and Engineering
Audiences
Alumni, Community, Faculty, Staff, Students