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.

Video Presentation

Current Group Members

GINSBOURGER, David
(Senior Researcher)
- website


Alumni

  • AZZIMONTI, Dario (Filippo)
  • KRITYAKIERNE, Tipaluck
  • MAITRE, Alan

Current Projects

Nothing to list

Recent Projects

Idiap has a new opening for an Internship position in Machine Learning for Energy Informatics
education — Sep 06, 2017

In view of a new collaboration between the Idiap Research Institute and the “Centre de Recherche Energétiques et Municipales” (CREM, www.crem.ch), we welcome applications for a 6- to 12-month internship. The intern will be co-supervised by the head of the Uncertainty Quantification and Optimal Design group at Idiap (PD Dr. David Ginsbourger) and by the director of CREM (Dr. Jakob Rager) and will work on statistical and machine learning approaches to optimization problems under uncertainty arising in energy planning.

Thesis award for Dario Azzimonti
education — 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.