Hello! After graduating with an MSc in Industrial Engineering applied to Energy, Transport and Environment at ISAE-SUPAERO in 2021 as well as an Msc in Management at Imperial College London, I worked for a year and a half as a Data Analyst at Onepoint. This experience led me to decide to change my career towards a career in research in Artificial Intelligence applied to health and biomedical imaging.
In 2022-2023, I studied the MVA (Mathematics, Vision, and Learning) Master at Ecole Normale Supérieure in Paris, a master in Artificial Intelligence with a particular focus on Applied Mathematics. I am currently doing an internship at NeuroPoly in Polytechnique Montréal focusing on building a foundational model for 3D medical images based on Implicit Neural Representations as well as working on various projects using deep learning for spinal cord segmentation or multiple sclerosis lesions segmentation on the spinal cord.
As a PhD student at Polytechnique Montréal, I am working on applied mathematics and deep learning methods for 3D medical imaging. I am particularly interested in data representation, shape analysis and multimodal approaches for medical image analysis. My interests lie at the intersection between medical research and artificial intelligence. Image segmentation and registration is a key step in medical imaging research. Working on algorithms using graph theory or mesh analysis is an interesting venue for the future of shape analysis. Recently, I have been very interested in the different methods used by models to encode a representation of the data in their latent space.
Amongst other topics, I am interested in biomedical imaging, cancer research, brain signal analysis, immunology, human vision, drug discovery, shape analysis and much more. I am also open to exploring other fields of research in health.