Curriculum Vitae
Download pdf

Positions

2017-present

Research engineer on the Eye2Brain project at CEMOSIS, Strasbourg, France

  • Development of new models to quantitatively describe metabolic connections between the eye and the brain
  • 3D/0D coupling between Feel++ and OpenModelica
  • HPC and cloud technology: MSO4SC project
 

2017-present

Active Developer in the Feel++ Project

  • Main developer on the reduced basis framework (C++)
  • Parallel programming and HPC
  • Scientific computing, Linear algebra, Numerical algorithms

Formation

2014-present

Ph.D.: The Reduced Basis Method Applied to Aerothermal Simulations at University of Strasbourg, France

  • Aerothermal simulations (finite element method, coupled non-linear system)
  • Implementation: Stabilization methods and turbulence model in Feel++
  • Model order reduction: Reduced Basis Method for non-linear problems
 

2012-2014

Master degree in Applied Mathematics at University of Strasbourg, France


Skills

Computer Science

  • Advanced C++ skills: meta-programming, MPI, scientific computing
  • Daily Use: cmake, boost, git, openmp, LATEX, Unix systems
  • Basics: python, slurm, java, html, matlab, fortran, docker, singularity

Applied Mathematics

  • Modeling: finite element method, CFD, coupled systems
  • Linear Algebra: preconditioning methods, iterative solvers
  • Model Order Reduction: Certified reduced basis, proper orthogonal decomposition, Proper generalized decomposition

Miscellaneous

  • Linguistics: French (mother tongue), English

Teaching

2015-present

Tutorials of mathematics in highly selective classes to prepare for the competitive exams to the French "Grandes Ecoles"

2014-2017

Lesson-Tuition of analysis L1 Sciences


Research Areas

Numerical analysis, Numerical method for partial differential equations, Model order reduction, Computational fluid dynamic, Mathematical model applied to medicine, Finite element method, HPC computing


Contacts

Adress

IRMA, UMR 7501
7 rue René-Descartes
Strasbourg, France

Phone

+333 68 85 02 19

LinkedIn
Top