PhD students:
- 11/2024 - : Virgile Bertrand, with R. Côte and E. Franck: Constructing the structural method for hyperbolic partial differential equations
- 11/2024 - : Daria Hrebenshchykova, with V. Dolean (Eindhoven) and S. Lanteri (Sophia-Antipolis): Building physics-based multilevel surrogate models from neural networks. Application to electromagnetic wave propagation
- 11/2024 - : Nicolas Pailliez, with E. Franck, L. Navoret and S. Pamela (Culham): Implicit neural representation and opertator learning for multi-scale physical problems
- 12/2023 - : Amaury Bélières-Frendo, with C. Dapogny (Grenoble), Y. Privat (Nancy) and C. Prud'homme: Shape optimization through learning
Post-doctoral researchers:
- 04/2025 - : Florian Salin, with C. Courtès, V. Ehrlacher (Paris), E. Franck, L. Navoret and Y. Privat (Nancy): Greedy training of neural networks
- 04/2025 - : Yanfei Xiang, with J. Aghili, J. Digne (Lyon), E. Franck and Y. Privat (Nancy): Generative models for the optimal control of PDEs and inverse problems
- 10/2023 - : Dinh Hung Truong, with E. Franck: Design of Neural Operators based on PINNs; applications to wave propagation and fluid dynamics
- 09/2021 - 08/2022: Pierre Gerhard, with Ph. Helluy: Explicit CFL-free Discontinuous Galerkin approximation of wave phenomena in the KOUGLOFV code: adaptation to distributed-memory computers using a domain decomposition approach
Involvement in PhD committees:
- 03/2025: Member of the PhD committee for Yen Chung Hung, University Savoie Mont Blanc
- 12/2022: Reviewer for Irene Gómez-Bueno's PhD thesis, University of Málaga, Spain
- 03/2022: Member of the PhD committee for Meissa M'Baye, Nantes University
Master's students:
- 2024-2025, Thesis (Master 2): Oussama Bouhenniche, with A. Thomann: Asymptotic-preserving and well-balanced high-order scheme for the Euler equations with gravity
- 2024-2025, Text study (Master 1): Franck Jacquard, Introduction to the hydrostatic reconstruction
- 2023-2024, Thesis (Master 2): Virgile Bertrand, with E. Franck: ScimBa: Combining Numerical Methods and Machine Learning for Solving PDEs
- 2023-2024, Thesis (Master 2): Daria Hrebenshchykova, with V. Dolean (Eindhoven) and S. Lanteri (Sophia-Antipolis): Multilevel and distributed Physics-Informed Neural Networks for the Helmholtz equation
- 2023-2024, Internship (Master 1): Marie Sengler, with E. Franck and J. Tryoen (Thales): Multiscale electrostatics and magnetostatics simulations on complex domains
- 2023-2024, Thesis (Master 2): Jérémy Pawlus, with A. Deleforge and E. Franck: Learning Green functions and reduced modeling for the Helmholtz equation
- 2023-2024, Thesis (Master 2): Alexis Schmitt, with K. Lutz: Introduction to the finite element method
- 2023-2024, Project (Master 2): Diana Sol Angel Fonseca-Hincapie, with E. Franck, L. Navoret and A. Thomann: Approximation of hyperbolic partial differential equations with discontinuous neural networks
- 2022-2023, Thesis (Master 2): Amaury Bélières-Frendo, with Y. Privat: Shape optimization through learning
- 2022-2023, Internship (Master 1): Jérémy Pawlus, with A. Thomann: Introduction to finite volume methods on unstructured grids; application to the Euler equations, implementation in Julia
- 2022-2023, Text study (Master 1): Pierre Balzano, with C. Courtès: Introduction to the analysis of hyperbolic systems
- 2022-2023, Text study (Master 1): Alexis Schmitt, Hamiltonian systems and symplectic integrators
- 2021-2022, Thesis (Master 2): Vincent Italiano, with H. Baty, E. Franck and V. Vigon: Reduced Order Modeling For Highly Nonlinear Partial Differential Equations Using Physics-Informed Neural Networks
- 2021-2022, Project (Master 2): Colin Holler, with J. Aghili: Structure-preserving methods for PDEs
- 2021-2022, Text study (Master 1): Mathéo Marquat, Introduction to the analysis of hyperbolic systems