ZUCKER Jean-daniel

Research Director
IRD
Unité de Modélisation Mathématique et Informatique des Systèmes Complexes UMMISCO (UMI209)

Expertise

Discover the specialized technical skills and disciplinary affiliations of our members, who represent the federated communities of the Arts & Humanities, Science & Engineering, and Medicine within the Sorbonne University Alliance.

Communities
Health, Medicine & Biology
Skills
Interpretability, Machine learning, Multi agent systems, Precision medicine

Activities

Overview the professional milestones, academic responsibilities, and international collaborations that drive our center’s double ambition to excel in both research and education.

Responsibilities

Lab Director

Selected publications

1) Aman Berhe, Guillaume Draznieks, Vincent Martenot, Valentin Masdeu, Lucas Davy, and Jean-Daniel Zucker. 2023. AliBERT: A Pre-trained Language Model for French Biomedical Text. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 223–236, Toronto, Canada. Association for Computational Linguistics.

2) Prifti, E., Y. Chevaleyre, B. Hanczar, E. Belda, A. Danchin, K. Clément, and J.-D. Zucker, Interpretable and accurate prediction models for metagenomics data. GigaScience, 2020. 9(3): p. giaa010. https://doi.org/10.1101/409144

3) Y. Chevaleyre, F. Koriche and J.-D. Zucker (2013). "Rounding Methods for Discrete Linear Classification." Journal of Machine Learning Research 28(1): 651–659. Saitta, L. and J.D. Zucker, Abstraction in Artificial Intelligence and Complex Systems. 2013, New York Inc.: Springer-Verlag.

4) Wang, J. and J.-D. Zucker, Solving Multiple-Instance Problem: a Lazy Learning Approach, in International Conference on Machine Learning, P. Langley, Editor. 2000, Morgan Kaufmann Publishers: Stanford, USA.