About
As a versatile Data Scientist, I bring extensive experience across diverse domains such as Earth Observation (Airbus Defence and Space), Spacecraft Rendezvous (IRT Saint Exupéry - RAPTOR), Neural Network Compression and Deployment (IRT Saint Exupéry - Confiance.ai), Anomaly Detection (Hexaglobe) and Natural Language Processing (IRT Saint Exupéry - RAKEL / ipso santé).
Education
-
Diplôme d’ingénieur – EPITA, Paris, France (2018–2021)
Specialized in Data Science and Artificial Intelligence (SCIA).
Main subjects: Mathematics, Algorithmics, and Data Science. -
Preparatory Classes (PCSI/PSI) – Lycée Alphonse Daudet, Nîmes, France (2016–2018)
Main subjects: Mathematics, Physics, and Engineering Sciences.
Work Experience
-
AI Research Engineer – IRT Saint Exupéry, Toulouse, France
-
AIxIA (Artificial Intelligence for Interference Analysis) – Ongoing
PM acting: Coordination of activities.
Leading the development of explainable language-based approaches for interference identification on multi-core processors. -
RAKEL (Robust and Accurate Knowledge Extraction by LLM) – Ongoing
Hallucination Detection for NOTAM Classification. -
RAPTOR (Robotic and Artificial Intelligence Processing Test On Representative Target) – 3 years (70%)
Leading the development of deep learning models for non-cooperative spacecraft rendezvous missions (Pose Estimation).
Design of a synthetic dataset. Optimization and deployment on space flight hardware. -
Confiance.ai (Grand Défi "Securing, certifying and enhancing the reliability of systems based on artificial intelligence") – 3 years (30%)
Development of a test bench for optimizing and evaluating neural networks on FPGAs using Vitis AI (AMD).
Study of semantic preservation for AI certification.
-
AIxIA (Artificial Intelligence for Interference Analysis) – Ongoing
-
Data Scientist – Airbus Defence and Space, Sophia Antipolis, France (End-of-studies Internship, 6 months, 2021)
Semantic segmentation of high-resolution satellite images using Deep Learning within an Agile team. -
End-of-study Project – ipso santé, Paris, France (2020–2021)
Unsupervised clustering of medical reports using Topic Modelling techniques with a team of 4. -
Data Scientist – Hexaglobe, Paris, France (Internship, 5 months, 2019–2020)
Anomaly detection using Deep Learning for a streaming service for both marketing analysis and breakdown prediction using Keras, Kafka, and Google Cloud Platform.
Public Scientific Communication
- On-board AI for Critical Applications, C. Marabotto, Robotop’IA 2025 / Workshop LIRMM. [pdf]
- An Evaluation Bench for the Exploration of Machine Learning Deployment Solutions on Embedded Platforms, E. Jenn et al., ERTS 2024. [pdf]
- Exploring AI-Based Satellite Pose Estimation: from Novel Synthetic Dataset to In-Depth Performance Evaluation, F. Gallet et al., CVPRW 2024 (AI4Space). [pdf]