Guillaume Charpiat
Scholar

Guillaume Charpiat

Google Scholar ID: SfBBevUAAAAJ
INRIA (Saclay)
Artificial intelligencestatistical learningcomputer visionshape statisticsoptimization
Citations & Impact
All-time
Citations
3,352
 
H-index
17
 
i10-index
29
 
Publications
20
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • Teaches courses such as Deep Learning in Practice (at the MVA master + CentraleSupelec), Information Theory (at the Paris-Saclay university AI master). Involved in various research projects, including deep learning for partially-observed dynamical systems, designing lighter architectures for generative models based on diffusion flows, etc.
Research Experience
  • Spent one year as a post-doc at the Max Planck Institute for Biological Cybernetics in Bernhard Schölkopf's team (statistical learning) from 2007 to 2008. Joined the Pulsar/St☆rs team (video understanding) at INRIA Sophia-Antipolis in 2008, and the TAO/TAU team (machine learning and optimisation) at INRIA Saclay in 2015. Has been the head of the Data Science department (of the LISN lab, Paris-Saclay University) since 2021.
Education
  • Defended his PhD thesis in computer vision within the Odyssee Team in December 2006; advisors were Olivier Faugeras and Renaud Keriven.
Background
  • Research interests include deep learning theory and applications, machine learning theory, statistical learning, and artificial intelligence. Main application areas are satellite imagery, human genetics, protein conformations, dynamical systems/fluid mechanics, etc.
Miscellany
  • Personal interests include presenting work through images and videos, with links provided for viewing.
Co-authors
0 total
Co-authors: 0 (list not available)