Postdoctoral fellow
Solid mechanics Laboratory
École Polytechnique, Palaiseau, France
Email:
Personal information
I hold a Ph.D. in computational mechanics from the University Paris-Saclay (ENS Paris-Saclay), where I worked at the LMPS (Laboratory of Mechanics Paris-Saclay). You can learn more about my background on my [CV].
My main research interest consists of solving highly non-linear problems using model-order reduction techniques such as the Proper Generalised Decomposition (PGD). I've recently become interested in hybridising classical model-order reduction methods with machine learning approaches. Combining tensor decomposition and interpretable neural networks enables efficient and robust solving of large non-linear problems. The ultimate goal of my research during this postdoctoral position is to achieve individualisation and real-time simulation of a lung model using model-order
reduction techniques thus going from theoretical tools to clinical application for patients with idiopathic pulmonary fibrosis (IPF).
Education
- 2020 - 2023 PhD - Laboratoire de Mécanique Paris-Saclay (UMR 9026, Université Paris-Saclay, CentraleSupélec, ENS Paris-Saclay, CNRS)
- 2019 - 2020 Master of science (M2R) - ENS Paris-Saclay / CentraleSupélec (MS2SC)
- 2018 - 2019 Scientific teaching qualification (agrégation de mécanique)
- 2017 - 2018 Master of science (1) - ENS Paris-Saclay (MMS)
- 2016 - 2017 Bachelor's degree in Engineering
- 2014 - 2016 MPSI-PSI* (Lycée Hoche, Versailles), Intensive two-year class of mathematics, physics and engineering sciences preparing for selective entrance examination to the French Grandes Ecoles
- 2011 - 2014 Baccalauréat (A-levels) - with first class honours (Lycée Hoche, Versailles)