Senior research scientist at Inria Grenoble Rhône-Alpes, project Mistis.
- Xerox Research Centre Europe,
- EDF R&D,
- CEA Cadarache.
- Vahinés, ANR MDCO (Masse de Données et Connaissances), 2008-12 This three-year project is called "Visualisation et analyse d'images hyperspectrales multidimensionnelles en Astrophysique" (VAHINES). It aims at developing physical as well as mathematical models, algorithms, and software able to deal efficiently with hyperspectral multi-angle data but also with any other kind of large hyperspectral dataset (astronomical or experimental). It involves the Observatoire de la Côte d'Azur (Nice), and several universities (Strasbourg I and Grenoble I). [link]
Figure 1. Left: Grain size of CO2 versus spectra projected on the first GSRIR axis (see Bernard-Michel et al. 2009a, 2009b). Right: Reconstructed map of grain size of CO2 on the Mars planet.
- Medup, ANR VMC (Vulnérabilité : Milieux et climats), 2008-12. This three-year project is called "Forecast and projection in climate scenario of Mediterranean intense events: Uncertainties and Propagation on environment" (MEDUP) and deals with the quantification and identification of sources of uncertainties associated with the forecast and climate projection for Mediterranean high-impact weather events. The propagation of these uncertainties on the environment is also considered, as well as how they may combine with the intrinsic uncertainties of the vulnerability and risk analysis methods. It involves Meteo-France and several universities (Paris VI, Grenoble I and Toulouse III). [link]
Figure 2. Map of the mean return-levels of daily rainfall(in mm) for a period of 10 years in the Cévennes-Vivarais area (see Gardes and Girard 2010)
- Movistar, ACI "masse de données" program, 2003-06. This three-year project involves team Lear from Inria, SMS from University Joseph Fourier and Heudiasyc from UTC, Compiegne. The project aimed at investigating visual and statistical models for image recognition and description and learning techniques for the management of large image databases.