My research themes as a teacher-researcher focus on experimental designs.
Experimental designs will enable the selection of experimental conditions under which experiments are carried out, depending on the objectives, in order to guarantee optimum quality of information. The new needs emerging from research laboratories and R&D departments have led me to focus my work on the development of new, innovative planning tools to provide a concrete response to unresolved problems. More specifically, I have focused on three main themes:
- reducing the number of tests (SMALL DATA)with the construction of experimental plans and/or the development of new analysis methods
– BIG DATA management and uniform experimental designs (Space Filling Design)
– the Quality-by-Design approach.
- Development of new Deep Learning and Active Deep Learning tools using Space Filling Design. This project is designed to remove scientific barriers by answering the following questions:
- How can we measure the relevance of an individual for the calibration of a deep learning model?
- How can the theoretical knowledge of experimental design be combined with deep active learning approaches?
IMBE – UMR CNRS 7263 / IRD 237 / Aix Marseille Université / Avignon Université.
IMBE, Faculté des Sciences et Techniques St-Jérôme – Service 421 – Av. Escadrille Normandie Niémen
F-13 397 Marseille, cedex 20 – France
Téléphone : +33 (0)4 13 94 49 28
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