My research aims to uncover hidden semantic relationships between data to improve information retrieval. I combine lexical (sparse) and semantic (dense) retrieval with graph-based models for tasks such as link prediction, data annotation and table search in data lakes. Applications include retrieval-augmented generation (RAG and GraphRAG), with a particular focus on grounding generated answers in verifiable sources.
I am an Associate Professor of Computer Science at Paris Nanterre University, where I teach data science in the Mathematics and Computer Science department, and a researcher in the Database Research Team at LIP6, Sorbonne University. I obtained my HDR from Sorbonne University in 2026.
Previously, I was at Isep (2017–2022), where I headed the Information Systems track and directed the Data Protection Officer Master’s program, and before that a postdoctoral researcher in the MiMove team at Inria. I have been a visiting scholar at the University of Leicester and UC Berkeley.
I am happy to hear from prospective PhD students and collaborators. Feel free to contact me.
Habilitation to Supervise Research (HDR): Data Management and Semantic Relationship Prediction in Complex Environments, 2026
Sorbonne University
PhD in Computer Science: A Self-healing Approach for Transactional Composite Services, 2015
Paris Dauphine University - PSL Research University
MSc in Computer Science, 2012
Simon Bolivar University
My research focuses on finding semantic relationships in heterogeneous data, including table discovery in data lakes, knowledge graph embedding and link prediction, and metadata alignment, and on using them for information retrieval and retrieval-augmented generation (RAG and GraphRAG).
Selected publications
In total: 6 journal articles (4 in Q1 venues), 2 book chapters and 30 papers in international conferences and workshops. The full list, with PDFs for most papers, is on Google Scholar and dblp.
PhD students
Other supervision
At Paris Nanterre University, since 2022
Previously