CV
Full CV: pdf
Professional experience
2020-…
Inria junior researcher, MIMESIS project-team
MLMS team, ICube laboratory, University of Strasbourg
2019-2020
Assistant professor, CEREMADE laboratory, MIDO, Université Paris-Dauphine
2018-2019
Postdoctoral position, LJLL, Sorbonne Université
Funding: Fondation Sciences Mathématiques de Paris
Supervision: Yannick Privat and Grégoire Nadin
Topic: “Optimisation problems arising in biology”
2016-2018
Postdoctoral position, I2M and LSIS, Aix-Marseille University
Funding: Labex Archimède
Supervision: Francesco Rossi and Morgan Morancey
Topic: “Control problems arising in crowd motion”
2015-2016
Full-time ATER (assistant professor, 192 h), LMB, Université de Franche-Comté
2012-2015
Teaching contracts (3 × 64 h), UFR-ST, Université de Franche-Comté
Education
2025
Habilitation à Diriger des Recherches (French accreditation to supervise research), University of Strasbourg
Subject: A priori and a posteriori estimates of finite element schemes and development of commands for some dynamic phenomena
Defended on 21 November 2025
2012-2015
PhD in applied mathematics, Université de Franche-Comté
Advisers: Farid Ammar Khodja, Boris Andreianov and Franz Chouly
Subject: Controllability of some systems governed by parabolic equations
Funding: Région Franche-Comté
Defended on 26 November 2015
2011-2012
Master of research: partial differential equations and numerical analysis, Université de Franche-Comté
Subject: Approximate controllability, optimisation and numerical convergence of a scheme for linear parabolic equations
2011
Agrégation of Mathematics (French national competitive examination): ranked 146th
2010-2011
Master of Professional Studies “History of science”, Université de Franche-Comté
Adviser: Stefan Neuwirth. Subject: “Les Sphériques de Ménélaüs”
2010
Capes of Mathematics (French national competitive examination): ranked 58th
Research interests
Optimal control problems applied to biology and medicine
Epidemiology, neuroscience, modelling, optimisation
Development of numerical tools for soft tissue simulation
Finite element methods, neural networks, a priori estimates, a posteriori estimates
Distinctions
2025-2027
RIPEC C3
2020-2023
PEDR Inria Starting
Projects and talks
The research projects are detailed on the Projects page, and the talks and events organised on the Research page — 30 invited conference talks and 37 invited seminar or workshop talks.
Scientific responsibilities
2021-…
Organiser of the MLMS and MIMESIS team seminar (sharing announcements and talks) https://mlms.icube.unistra.fr/en/index.php/Seminars
2022-…
Member of the centre committee of the Inria Nancy Grand Est centre
2022
Member of the hiring committee for Inria junior researchers at the Nancy Grand Est centre
2014-2016
PhD student representative at the Carnot-Pasteur doctoral school, Bourgogne Franche-Comté
2014-2016
Head of the PhD student seminar, LMB, https://lmb.univ-fcomte.fr/doctorat-au-lmb/seminaire-des-doctorants/
Reviewer for SEMA SIMAI, Journal of Differential Equations, Systems & Control Letters, ESAIM: COCV, Mathematics of Control, Signals and Systems, IEEE Transactions on Control Systems Technology, Journal of Dynamical and Control Systems, North Western European Journal of Mathematics, Evolution Equations & Control Theory, Advanced Modeling and Simulation in Engineering Sciences, Radon Series on Computational and Applied Mathematics, Mathematical Control and Related Fields, Nonlinear Analysis: Real World Applications.
Teaching
2023-2024
- Uncertainty quantification, lectures and exercises (8 h) — MSc 2 CSMI, University of Strasbourg. Uncertainty quantification, sensitivity analysis, kriging, propagation.
- Scientific computing, lectures and exercises (10 h) — MSc 2, agrégation preparation in mathematics, University of Strasbourg. Interpolation, nonlinear equations, integration, optimisation, differential equations, partial differential equations.
- Optimal control, lectures and exercises (28 h) — MSc 2 CSMI, University of Strasbourg. Controllability of ODEs, Pontryagin’s maximum principle, adjoint method for PDE constraints.
- Optimisation, lectures and exercises (28 h) — MSc 1 CSMI, University of Strasbourg. Existence and uniqueness of minimisers, optimality conditions, numerical methods.
2022-2023
- Uncertainty quantification, lectures and exercises (17 h) — MSc 2 CSMI, University of Strasbourg. Uncertainty quantification, sensitivity analysis, kriging, propagation.
- Scientific computing, lectures and exercises (16 h) — MSc 2, agrégation preparation in mathematics, University of Strasbourg. Interpolation, nonlinear equations, integration, optimisation, differential equations, partial differential equations.
- Numerical analysis techniques 2, lectures (10 h) — BSc 3 mathematics, University of Strasbourg. Numerical integration, families of classical polynomials, eigenvalue computation.
2021-2022
- Uncertainty quantification, lectures and exercises (17 h) — MSc 2 CSMI, University of Strasbourg. Uncertainty quantification, sensitivity analysis, kriging, propagation.
- Numerical analysis techniques 1, exercise classes (17 h) — BSc 3 mathematics, University of Strasbourg. Matrix analysis, iterative methods, gradient methods, interpolation, least squares.
- Numerical analysis techniques 2, lectures (10 h) — BSc 3 mathematics, University of Strasbourg. Numerical integration, families of classical polynomials, eigenvalue computation.
2020-2021
- Uncertainty quantification, lectures and exercises (17 h) — MSc 2 CSMI, University of Strasbourg. Uncertainty quantification, sensitivity analysis, kriging, propagation.
- Computer science, exercise classes (34 h) — BSc 3 mathematics, University of Strasbourg. Introduction to C++, algorithmic complexity and functions in C++, verification, sorting.
- Numerical analysis techniques 1, exercise classes (17 h) — BSc 3 mathematics, University of Strasbourg. Matrix analysis, iterative methods, gradient methods, interpolation, least squares.
- Numerical analysis techniques 2, lectures (10 h) — BSc 3 mathematics, University of Strasbourg. Numerical integration, families of classical polynomials, eigenvalue computation.
2015-2016
- Algebra, lectures and exercise classes (104 h) — BSc 1, science and engineering. Logic, set theory, polynomials, maps, linear systems, matrices.
- Mathematics, exercise classes (24 h) — first year of engineering school (ISIFC). Continuity, differentiability, linear algebra, Taylor expansions, differential equations, extrema.
- Numerical methods, computer labs (8 h) — first year of engineering school (ISIFC). Interpolating polynomials, solving linear systems, finite differences, finite elements.
- Internship supervision (10 h) — engineering school (ISIFC).
- Elements of algebra, exercise classes (20 h) — BSc 2, computer science, physics, chemistry. Arithmetic, order and equivalence relations, groups and rings.
- Approximation and signals, computer labs (12 h) — MSc 1, modelling and statistics. Fourier series, Hilbert bases, wavelets.
- Optimisation and linear programming, computer labs (12 h) — MSc 1, modelling and statistics. Minimisation of functionals and solution of linear systems.
2014-2015
- Mathematics, exercise classes (34 h) — BSc 1, life and earth sciences. Study of functions, computation of integrals and differential equations.
- Mathematical tools, exercise classes (20 h) — BSc 2, computer science. Taylor expansions and study of sequences.
- IREM mathematics/physics working group and training courses
2013-2014
- Algebra, lectures and exercise classes (52 h) — BSc 1, science and engineering. Logic, set theory, polynomials, maps, linear systems, matrices.
- IREM mathematics/physics working group and training courses
2012-2013
- Analysis, lectures and exercise classes (52 h) — BSc 1, science and engineering. Study of functions, computation of integrals, differential equations, Taylor expansions.
- IREM mathematics/physics working group and training courses
2011-2012
- Analysis, lectures and exercise classes (52 h) — BSc 1, science and engineering.
- Bilinear algebra, exercise classes (40 h) — BSc 2 mathematics. Symmetric bilinear forms, inner products and Hermitian forms.
Computing skills
Python, Maple, Matlab, Scilab, FEniCS
Languages
French (native), English and German: good level