Description

I hold a PhD in Machine Learning and degrees from ENSAE ParisTech and École Polytechnique.

I am eager to apply my expertise in AI to innovative projects, with experience in various domains of industry including healthcare, finance, insurance, energy, and retail.

Domaines d’expertise

Langues

Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Espagnol
Capacité professionnelle limitée

Préférences en matière de lieu de travail

Accepte de travailler sur site

Paris (jusqu’à 50 km)

IBISC laboratory, Paris-Saclay University
PhD candidate in Machine Learning
SANTÉ & BIEN-ÊTRE
février 2022 - juin 2025 (3 ans et 4 mois)
Évry, France
IBISC is a laboratory at the Paris-Saclay University that deals with computer science
and bioinformatics.
• Challenge: long RNA secondary structure prediction including pseudoknots
• Developed DivideFold: a ”divide-and-conquer” method to recursively partition
RNA using a deep convolutional network
• Deployed a web server to facilitate the use of DivideFold by biologists
• Improved model performance through the implementation of new data
augmentation strategies for RNA sequences and secondary structures
(mutation, insertion, deletion, inversion, translocation, reverse complementing)
• Published two papers
• Gave oral presentations at two international conferences
• Taught programming to undergraduate (L1–L2) and master’s (M2) students
• Organized, presented, and served on the junior committee for the JDSE 2022
conference
Bioinformatique Deep Learning Recherche Capacité rédactionnelle Capacité d'analyse
Margo
Data engineer consultant
BANQUE & ASSURANCES
avril 2021 - octobre 2021 (6 mois)
92800 Puteaux, France
• Trained in data engineering (Databricks Academy)
• Migrated data ingestion jobs to the Azure cloud
• Implemented and tested Databricks data pipelines on the cloud
Développement
Self-employed
Freelance data scientist
SANTÉ & BIEN-ÊTRE
octobre 2020 - avril 2021 (6 mois)
• Classified biomedical images with computer vision for breast cancer detection
(invasive cancer, in situ cancer, or healthy tissue)
• Worked closely with the client to understand their needs and communicate
technical results in an accessible way
Computer Vision Deep Learning imagerie médicale