About

I graduated from CPE Lyon in electronics and computer science and received a PhD in computer science from the ERIC lab (Université Lumière Lyon 2), under the supervision of Julien Velcin and Adrien Guille. My research integrates graph machine learning (GML) and natural language processing (NLP), with applications in information retrieval (IR) and recommender systems. During my studies, I worked as a machine learning developer at Digital Scientific Research Technology, contributing to Peerus, a web application designed to help researchers monitor scientific literature. I later completed a postdoctoral fellowship at LIS (Aix-Marseille Université) in the TALEP team, focusing on using language models and graph algorithms to explore archives in the humanities.

My expertise has led me to work on various projects, including:

• Building a knowledge graph (KG) for the fashion industry at Farfetch, using computer vision, graph neural networks (GNNs), and NLP models. I also developed recommender systems powered by GNNs on this knowledge graph.
• Fine-tuning large language models (LLMs) for automatic code generation in business intelligence tools at Pigment. [Video]
• Predicting drug-drug adverse events with graph neural networks, applying causal machine learning models in clinical studies, and developing an LLM-based assistant for real-world evidence exploration at Novartis. [Video].
• Currently, I am designing and implementing an AI-agent-based application (entrepreneurship) to help small businesses mitigate their carbon footprint .

Passionate about applying artificial intelligence to real-world challenges, I am eager to explore new and impactful AI applications.

For contact information, visit this page. My CV is available here.