Summary
Working on deep learning for biomedical images
Professional experiences
Doctoral student
ECOLE POLYTECHNIQUE
From November 2023 to Today
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
From March 2023 to September 2023
Deep learning research in 3D tumor segmentation.
Research intern
TELECOM PARIS
From May 2022 to June 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
From April 2022 to March 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
From September 2020 to April 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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