2018  2021 
PhD in Mathematics
Hybrid HighOrder method for complex problems in fluid mechanics
Supervised by Daniele A. Di Pietro, ACSIOM team, IMAG laboratory, Montpellier, France
Description
Hybrid HighOrder methods are a recent and highly innovative class of new generation numerical methods for PDEs that aim at overcoming the limitations of traditional discretization methods such as Finite Element or Finite Volumes. Their most prominent features include:
 support of general polytopal meshes in arbitrary space dimension,
 arbitrary approximation order,
 compliance with the physics,
 reduced computational cost thanks to hybridization, static condensation, and compact stencil.
The goal of this PhD thesis is to develop, analyze, and implement novel HHO discretizations of complex problems in fluid mechanics. We specifically aim at treating generalized Newtonian fluids where the shear stress function exhibits a nonlinear dependency on the shear rate, and possibly include the challenging variable density case. The convergence analysis will rely on both standard error estimates and compactness arguments. This will require to develop discrete functional analysis lemmas whose interest will go beyond applications to computational fluid mechanics. The implementation will rely on the spafedte library, and will benefit from the latest advances in C++ programming.
Formations (174h)
Research and integration
 Fluid and kinetic description of plasmas at Paris (Roch Smets, Gérard Belmont, Filippo Pantellini)
 Introduction to theories beyond the Standard Model of particle physics (Frigerio Michele)
 Eccomas Congress 2020 & 14th WCCM, Virtual event
 XXIièmes Louis Antoine Numerical Analysis day at Rennes (Robert Eymard, Francis Filbet)
 MOOC Research integrity in scientific professions
Teaching
 MOOC Training to teach in higher education
 How to have an innovative pedagogy? (Sylvain Rouanet)
 Why and how to develop interactive courses? (Sylvain Rouanet)
 Introduction to teaching tools for higher education (Sébastien Balme)
 Prepare, organize and conduct a course (Nathalie Berda)
 Public speaking (Marc Dumas)
Miscellaneous
 Level 1 Prevention and Civic Assistance training

2018 
Ranked 1st place in Mathematics in the competitive admission exam for the i2S doctoral school, Montpellier, France

2016  2018 
Master's degree in Mathematics
MANU (Modelization and numerical analysis of PDEs), University of Montpellier, France
with distinction « Très Bien »
Courses
Internship (6 months) : HybridHigh Order method for creeping flows of powerlaw fluids
Supervised by Daniele A. Di Pietro, ACSIOM team, IMAG laboratory, Montpellier, France

2013  2016 
Bachelor's degree in Mathematics
Research option
University of La Rochelle, France
with distinction « Bien »

2013 
Baccalaureate
STL (Sciences et Technologies de Laboratoire) option
Lycée de la Venise Verte, Niort, France
with distinction « Assez Bien »
