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Uncertainty Quantification and Optimal Design

The Uncertainty Quantification and Optimal Design group focuses on quantifying and reducing uncertainties in the context of hi-fidelity models, with a main expertise on Gaussian Process methods and sequential design of computer experiments for optimization, inversion, and related problems. Application domains notably include energy and geosciences, with collaborations ranging from safety engineering to hydrology and climate sciences.

Current Group Members

Group Members

David Ginsbourger (Permanent Senior Researcher)
Alan Maître (intern)
Dario Azzimonti (UniBE PhD student)
Sébastien Marmin (Visiting PhD student)
Katalin Siegfried (Visiting MSc student)
Cédric Schärer (Visiting MSc student)

Alumni

Tipaluck Krityakierne (Postdoc 2015-2016)

News

Thesis award for Dario Azzimonti Jan 09, 2017
Dr. Dario Azzimonti was awarded the C. Moser Award for outstanding Ph.D. or M.Sc. theses within the Institute of Mathematical Statistics and Actuarial Science of the University of Bern.
Idiap has a new opening for an internship position on extreme value analysis for non-stationary time series with application in climate sciences Feb 24, 2016
The Idiap Research Institute invites applications for one internship position within the Uncertainty Quantification and Optimal Design group to work on extreme value analysis for non-stationary time series with application in climate sciences.
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