My research is broadly situated within computer vision and aims primarily at modeling visual perception through multimodal and multiscale imaging, as well as machine learning and artificial intelligence tools. To this end, I have recently focused on  the acquisition, processing, and analysis of multidimensional images. This involves either geometric and photometric modeling of surface appearance or information extraction (physiological parameters) when dealing with living surfaces (biomedical applications) . Indeed, as a logical continuation of my work on color and multispectral imaging as an important part of human visual perception, I am currently interested in a more comprehensive integrated modeling (in terms of both appearance and function) of surfaces.  This involves the integration of several modalities and naturally implies that I address the scientific barriers of the appropriate representation of data, the contribution of machine learning and artificial intelligence tools and the extension/adaptation of classical methodologies for the understanding of visual perception phenomena while putting them in tension with application expectations, particularly in heritage, industry and biomedicine.