My researches are at the intersection of applied mathematics and inertiel confinement fusion (ICF), and more precisely are about the numeric simulations of plasma physics. Last years, I explored the use of deep learning in the field of computational physics:

• Finite volumes for continuum mechanics.
• Monte-Carlo methods for particules transport.
• ICF numeric simulations on supercomputers.
• Deep learning for atomic physics. PHd of Sébastien Thévenin in progress “Machine learning methods for models of turbulence in fast transition phases”. Collaboration in progress with the LLNL (Lawrence Livermore National Laboratory) in California “Using deep learning in a simulation program”.