Bertrand Iooss

Bertrand Iooss



Bertrand obtained a Master in Statistics and Random Models in Finance in 1995 from University Paris VII. Further he defended (1998) his Ph.D thesis in Geostatistics at the Paris School of Mines, and his HDR (Habilitation à Diriger les Recherches) in Statistics at the University Toulouse III (2009). From 2000 to 2002, he worked as a research-engineer at the Institut Français du Pétrole in the Geophysics Division on seismic inverse problems. From 2002 to 2010, he was a research-engineer at the Nuclear Energy Division of CEA Cadarache, working mainly on sampling strategies and uncertainty/sensitivity analysis methods for nuclear safety issues. Since 2010, he works as a senior researcher at Electricité de France (EDF), Research and Development Division, Department of Performance, Industrial Risk, Monitoring for Maintenance and Operations. He managed (2015-2021) a CEA-EDF-Framatome research project on “Uncertainty quantification and machine learning” techniques for nuclear safety and operational process optimization. During twelve years (2008-2020), he was also the co-leader of the French research group (CNRS) on “Stochastic methods for computer experiments” (

His research interests involve the design, analysis, modeling and uncertainty management in computer experiments, as well as the topics of interpretability and validation of machine learning techniques (more recently). Bertrand has provided several Master courses in French engineering schools, supervised or co-supervised around 15 PhD thesis students and 40 students in Master internships. He has published around 70 papers in international journals and is the maintainer of two R packages on sensitivity analysis (sensitivity) and structural reliability (mistral). He is the co-author of two books on global sensitivity analysis techniques (one in French and one in English published by SIAM editor in 2021).

  • Applied and industrial statistics
  • Design and modeling of numerical experiments
  • Uncertainty and sensitivity analysis of computer models
  • Machine learning - Explainability and interpretability
  • R software
  • Workshops organization
  • Training in international research schools
  • Habilitation Thesis in Applied Mathematics, entitled 'Contributions to the uncertainty management in numerical modelisation: Wave propagation in random media and analysis of computer experiments', 2009

    Université Paul Sabatier, Toulouse, France

  • PhD in Geostatistics, entitled “Statistical tomography in seismic reflection: Estimation of a stochastic velocity model”, 1998

    Paris School of Mines, Fontainebleau, France

  • Master 2 in Statistics and Random Models in Finance, 1995

    Université Paris VII, Paris, France