David Ginsbourger
Idiap + IMSV

Biographical sketch:

I am working mainly as a permanent senior researcher at Idiap Research Institute (Martigny, Switzerland) where I am heading the Uncertainty Quantification and Optimal Design group, and I am also holding since 2018 a titular professorship at the University of Bern, where I have been employed as a Dozent I in the Institute of Mathematical Statistics and Actuarial Science (Department of Mathematics and Statistics) since my habilitation. Besides, I am a member of the Oeschger Center for Climate Change Research of the University of Bern, on the scientific committees of the GDR Mascot-num and the ANR project RISCOPE, and serving as a scientific adviser to the OQUAIDO chair in applied mathematics.

I defended my venia docendi (habilitation) in Statistics and Applied Probability before the Faculty of Science of the University of Bern in 2014 and my PhD in Applied Mathematics at the Ecole des Mines de Saint-Etienne in 2009. Previous to that, I obtained a double graduate diploma from Ecole des Mines de Saint-Etienne and Berlin Technical University(2005), a research master's degree in Applied Mathematics jointly awarded by Jean Monnet University and Ecole des Mines de Saint-Etienne (2005), and a licence in Mathematics from Joseph Fourier University, Grenoble (2002).

From 2008/2009, I worked as an assistant and a scientific collaborator, respectively in the Institute of Mathematics and the Centre for Hydrogeology and Geothermics (Stochastic Hydrogeology Group), University of Neuchatel, before starting to work as Senior Assistant (2010) and then Dozent (2014) at the Institute of Mathematical Statistics and Actuarial Science of the University of Bern. The Uncertainty Quantification and Optimal Design group started at Idiap in 2015.

A significant part of my research deals with Gaussian random field modelling and adaptive design of experiments, with a focus on bayesian global optimization and related topics such as Bayesian set estimation. Further interests include design and estimation of covariance kernels and parameters, as well as connections between Kriging and functional analysis approaches (noatbly the RKHS theory). From the real-world application side, I have been working with a number of colleagues both from engineering and from geosciences. Recently, my team and I have started collaborations with climate scientists.