I am a PhD candidate at IP Paris, France, working toward making AI more accessible for biology researchers and practitioners. My research interests lie at the frontier between AI, biology, and frugal computing: I hope to accelerate research in biology by lowering the (computational) resource requirement for running state of the art models and analysis techniques. Currently, I focus on the analysis of very large multi-resolution images.

Research

  • Toward a Metal Usage Effectiveness metric in Data Centers: A Study
    Marie Reinbigler, Rosalie Martin
  • Artificial intelligence workflow quantifying muscle features on Hematoxylin–Eosin stained sections reveals dystrophic phenotype amelioration upon treatment
    Marie Reinbigler, Jérémie Cosette, Zoheir Guesmia, Simon Jimenez, Catalin Fetita, Elisabeth Brunet & Daniel Stockholm

Curriculum

  • PhD Research Internship at Adobe Research March 2024 - August 2024
    Advisor: Rosalie Martin
  • PhD Candidate at IP Paris 2021 - ongoing
    Member of the Parallel and Distributed Systems Group
    Advisors: Elisabeth Brunet and Prof. Catalin Fetita
  • Visiting PhD Student at EPFL 2022 - 2023
    Working with Prof. Anne-Marie Kermarrec
  • MSc at IP Paris 2020 - 2021
    High Performance Data Analytics
  • Engineering Degree at Telecom SudParis 2018 - 2021
    Ranked 1st out of 200 students

Awards & Funding

Funding:

  • IP Paris Excellence Scholarship (Hi! Paris/ANR IA) 2021

Awards

Grants

Talks & Presentations

Teaching

Lecturer

  • CSC3102: Introduction to Operating Systems
  • CSC4103: System Programming

Teaching Assistant

  • CSC3101: Algorithmics and Programming Language
  • CSC4102: Introduction to Software Engineering for Object-Oriented Applications

Service

Supervised Students

  • Nathan Feret et Malek Hammou 2023-2024
    Project Title: Ordonnancement de l’analyse pyramidale d’images biologiques multi-résolution dans un contexte d’exécution frugal
  • Arthur Sabin 2022-2023
    Project Title: Combining knowledge graphs and graph-based neural networks for multi-resolution biological image classification
  • Raphaëlle Thieux 2022
    Project Title: GNN on multi-resolution data - building and evaluation