Ségolène Martin
I am working as a postdoctoral researcher at TU Berlin (Math+ project), in the image analysis team headed by Prof. Gabriele Steidl and in collaboration with Prof. Hanno Gottschalk. My current research is at the intersection of optimization, optimal transport and generative learning, with applications to image processing and computer vision.
Prior to that, I was a PhD student in applied mathematics at CentraleSupélec, Université Paris-Saclay, in the CVN / OPIS Inria team. My PhD was under the supervision of Prof. Jean-Christophe Pesquet (CVN, CentraleSupélec) and Prof. Ismail Ben Ayed (ILLS, ETS Montréal). I defended my thesis Variational methods for large scale data problems in imaging on January 26th, 2024. You can find the manuscript here.
Research interests
- Large-scale continuous optimization
Majoration-Minimization & proximal algorithms, Expectation-Maximization, convergence theory - Inverse problems for image processing
Image restoration and reconstruction, PSF estimation - Image classification
Clustering and few-shot optimization-based methods, unbalanced few-shot, transductive learning - Text-vision models
Zero and few-shot classification with CLIP - Image generation
Flow-based models, GANs
Education
- PhD in Applied Mathematics, 2020-2024
CentraleSupélec, Université Paris-Saclay - Master in Mathematics, Vision and Learning (MVA), 2019-2020
École Normale Supérieure Paris-Saclay - Agrégation in Mathematics, 2018-2019
École Normale Supérieure Paris-Saclay - Bachelor's Degree in Fundamental Mathematics, 2016-2017
École Normale Supérieure Paris-Saclay