Celebrating New PhDs from the BL.Research Team!

At Berger-Levrault, research is more than a mission—it’s a shared adventure. As the new academic year begins, we are proud to celebrate the success of four of our colleagues from the BL.Research team, who have reached a major milestone in their scientific journeys: the defense of their doctoral theses.

These achievements are the result of years of dedication, curiosity, and collaboration between our researchers and partner laboratories. Together, they contribute to advancing knowledge while addressing real-world challenges at the intersection of academia and industry.

Our new doctors in 2024/25:

• Camille Gosset – defended her thesis in September 2024, in partnership with LIRMM, on “Methods and Models for the Automated Development of Knowledge Graphs in the Legal Field.”
  • Gosset, C. (2023). Classification de documents métiers pour l’aide à l’extraction et la classification de relations lexico-sémantiques typées et pondérées. Conférence Nationale sur les Applications Pratiques de l’Intelligence Artificielle (APIA), 37–40. https://pfia23.icube.unistra.fr/conferences/apia/Articles/APIA2023_paper_6869.pdf
  • Gosset, C., Billami, M. B., Lafourcade, M., Bortolaso, C., & Derras, M. (2022). Création et validation de représentations vectorielles pour des relations lexico-sémantiques : application à l’identification/classification de relations à partir d’un corpus métier. Conférence Francophone Sur l’Extraction et La Gestion Des Connaissances (EGC2022). https://editions-rnti.fr/?inprocid=1002768
  • Gosset, C., Billami, M. B., Lafourcade, M., Bortolaso, C., & Derras, M. (2021). Extraction automatique de relations sémantiques d’hyperonymie et d’hyponymie dans un corpus métier (Automatic extraction of hypernym and hyponym relations in a professional corpus). Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale, 162–170. https://aclanthology.org/2021.jeptalnrecital-taln.15
• Nicolas Ringuet – defended his thesis in November 2024, in partnership with LIFAT, on “Modeling, Exploration, and Explainable Co-Construction of Life Paths.”
  • Ringuet, N., Marcel, P., Labroche, N., Devogele, T., & Bortolaso, C. (2022). Modeling Lifelong Pathway Co-construction. In J. Ralyté, S. Chakravarthy, M. Mohania, M. A. Jeusfeld, & K. Karlapalem (Eds.), Conceptual Modeling (pp. 130–144). Springer International Publishing. https://doi.org/10.1007/978-3-031-17995-2_10
  • Chanson, A., Devogele, T., Labroche, N., Marcel, P., Ringuet, N., & T’Kindt, V. (2021). A Chain Composite Item Recommender for Lifelong Pathways. In M. Golfarelli, R. Wrembel, G. Kotsis, A. M. Tjoa, & I. Khalil (Eds.), Big Data Analytics and Knowledge Discovery (Vol. 12925, pp. 55–66). Springer International Publishing. https://doi.org/10.1007/978-3-030-86534-4_5
  • Ringuet, N. (2021). Challenges in Lifelong Pathways Recommendation. In L. Bellatreche, M. Dumas, P. Karras, R. Matulevičius, A. Awad, M. Weidlich, M. Ivanović, & O. Hartig (Eds.), New Trends in Database and Information Systems (pp. 310–316). Springer International Publishing. https://doi.org/10.1007/978-3-030-85082-1_28
• Hamza Safri – defended his thesis in June 2025, in partnership with Inria, on “Federated Learning for the IoT: Application for Industry 4.0.”
  • (2024) Towards Efficient Belt Conveyor Maintenance: Leveraging Federated Learning: https://ieeexplore.ieee.org/document/10839891
  • (2022) A Federated Learning Framework for IoT: Application to Industry 4.0: https://ieeexplore.ieee.org/abstract/document/9825974
  • (2022) Towards Developing a Global Federated Learning Platform for IoT: https://ieeexplore.ieee.org/abstract/document/9912211
• Julien Breton – defended his thesis in June 2025, in partnership with IRIT, on “Extraction and Formalization of Knowledge on Regulatory Industrial Maintenance from Semi-Structured Corpora.”
  • Breton, J., Billami, M. B., Chevalier, M., & Trojahn, C. (2025). Empowering CamemBERT Legal Entity Extraction With LLM Boostrapping. In M. Alam, M. Rospocher, M. van Erp, L. Hollink, & G. A. Gesese (Eds.), Knowledge Engineering and Knowledge Management (pp. 86–101). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-77792-9_6
  • Breton, J., Billami, M. B., Chevalier, M., & Trojahn, C. (2024). Leveraging Semantic Model and LLM for Bootstrapping a Legal Entity Extraction: An Industrial Use Case. 20th International Conference on Semantic Systems (Semantics2024). https://2024-eu.semantics.cc/
  • Breton, J., BILLAMI, M. B., Trojahn, C., & Chevalier, M. (2022). Semantic Model for the Legal Maintenance: the Case of Semantic Annotation of France Legislative and Regulatory Texts. Proceedings of the International Workshop on Methodologies for Translating Legal Norms into Formal Representations, 110–123. https://web.archive.org/web/20230117144317/https://research.nii.ac.jp/~ksatoh/LN2FRproceedings.pdf. https://research.nii.ac.jp/~ksatoh/LN2FRproceedings.pdf

Thank you to all our academic partners for their commitment to these fruitful collaborations, which strengthen the ties between research and industry.

Creating innovation inspired by industrial issues

These theses were supported by the CIFRE program, an initiative of the Ministry of Higher Education and Research, managed by ANRT. The program plays a vital role in connecting academic excellence with industrial innovation—helping to transform research into impact.

Because at Berger-Levrault, we believe in fostering talent, encouraging bold ideas, and supporting applied research with conviction. To those who are about to defend their thesis this year, and to those just beginning their doctoral journey: we look forward to seeing where your research will take you!