The UQPhysAI Chair will improve fundamental understanding and develop robust and widely applicable algorithms for two cornerstones of uncertainty quantification: sensitivity analysis and active learning with Bayesian models.
For sensitivity analysis, the focus will be on causal analysis and the large size and complexity of inputs and outputs.
With regard to Bayesian models and active learning, the Chair will focus on nested and coupled environments, and on exploiting new and more diverse techniques for quantifying uncertainties.
Methodological developments will be fed by and applied to realistic problems and data for physical and artificial intelligence systems, in collaboration with industrial partners: ONERA, Airbus, Liebherr and Vitesco.