Résumé
Working on deep learning for biomedical images
Expériences professionnelles
Doctoral student
ECOLE POLYTECHNIQUE
De Novembre 2023 à Aujourd'hui
Machine learning enabled quantification of cellular nuclear deformations on microgroove substrates. Advisors: Abdul Barakat (LadHyX, Ecole Polytechnique), Elsa Angelini (LTCI, Telecom Paris)
Research intern
Dassault Systèmes
De Mars 2023 à Septembre 2023
Deep learning research in 3D tumor segmentation.
Research intern
TELECOM PARIS
De Mai 2022 à Juin 2022
Deep learning on MRI, CT, CXR datasets with different windowing settings to study the optimalities of VOI prior in full acquisition dynamics.
Research intern
ECOLE POLYTECHNIQUE
De Avril 2022 à Mars 2023
Segmentation of myelinated axons and dendrites in THG images. Modeling collagen/myosin/tubulin fiber orientations in pSHG images. Worked on bioimageloader, a python library for wrapping bioimage datasets in a unified interface for machine and deep learning applications.
Research intern
ECOLE POLYTECHNIQUE
De Septembre 2020 à Avril 2021
Created an algorithm using Fourier-Motzkin elimination to improve the physical interpretability of exact linear reductions of rule-based biochemical models.
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