Givaudan est un fabricant suisse de parfums, d’arômes et d’ingrédients actifs cosmétiques. En 2008, elle est devenue la plus grande entreprise de l’industrie de la parfumerie et des arômes. Givaudan détient 25% de parts de marché d’une industrie estimée globalement à 17 milliards de francs suisses.
Recherche : Data Sciences dedicated to flavours and fragrances.
In flavours and fragrances domains, massive data are complex and are pushing technical limits in many areas, specifically in decision-making and optimization.
The objective of this collaborative work between Givaudan and CentraleSupélec is to face the challenges “Data-to-Knowledge” and “Data-to-Decision” in an integrated way through cutting edge research. More precisely, one aims at developing breakthrough techniques for dealing with high-dimensional and multi-scale data. Givaudan has and creates, in its activities domain, massive data of different natures.
It is essential to exploit these data to improve the understanding or to provide innovative and challenging techniques in the perfumery. Mainstream statistical models and decision-making algorithms are challenged by such heterogeneous, multi-scale, complex, incomplete and/or uncertain data. In order to generate knowledge, build models and make informed decisions, statistical validity, robustness, computational tractability and causal modelling are mandatory. This is the scientific purpose of this Chair : developing advance Machine Learning techniques adapted to such data.
Titulaire : Frédéric Pascal du laboratoire L2S
Partenaire : Givaudan