I am a researcher in the domain of Bayesian Design and Analysis of Computer Experiments (Bayesian DACE).
I teach Bayesian statistics at CentraleSupélec. I am also the coordinator of data science projects. In the past, I have also taught functional analysis and probability theory.
Design and analysis of computer experiments is about using statistical approaches to problems such as approximation, uncertainty quantification, optimization… involving computer programs (or simulators) that emulate physical systems (see, e.g., Santner 2003).
My work relies on the theory of Bayesian sequential decision. In the domain of computer experiments, the Bayesian approach starts with a prior distribution that represents our prior belief about the structure of the computer model. The use of this approach for computer experiments appeared in the 1980s (see the seminal article by Sacks et al. 1989).
My activities are reflected in my current implication in the stirring committees of the GdR MascotNum and the PGMO program of the FMJH.
Please refer to the Research tab above for more information about my research work
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