Judith Abécassis is a research scientist (ISFP) in the Soda team at Inria Saclay, where she bridges statistical methods in causal inference with medical applications to deliver actionable insights that enhance patient care. Collaborating closely with medical experts, she analyzes real -world observational data from the AP-HP Clinical Data Warehouse - focusing on diabetes, inflammatory diseases, and strokes - as well as administrative claims data. Her work aims to translate complex data into evidence-based recommendations for clinical decision-making. She holds a PhD in Bioinformatics from the Center for Computational Biology at Mines ParisTech and the RT2 Lab (Tumor Residue and Treatment Response) at Institut Curie, where she specialized in high-throughput sequencing data analysis from cancer genomes.

Augusto Anguita-Ruiz is a Junior Research Leader at the Barcelona Institute for Global Health (ISGlobal) and an Adjunct Professor at the Faculty of Pharmacy, University of Barcelona. He holds a PhD in Nutritional Biochemistry from the University of Granada. His research focuses on the integration of exposome and multi-omics data to understand the early-life origins of obesity, insulin resistance, and metabolic dysfunction. He applies explainable artificial intelligence (XAI) and systems biology approaches to characterize molecular trajectories and identify predictive biomarkers across the life course. He has published over 40 peer-reviewed articles and participated in large-scale European projects such as ATHLETE and IHEN. His recent work includes the coordination of EXOMAIR, a national project combining exposome profiling with AI to inform precision prevention strategies in pediatric populations.

Professor Marc Chadeau-Hyam is an applied statistician with expertise in translational research devising reproducible and interpretable methods for the characterisation of the Exposome via omics profiling and integration. He has been involved as lead statistician in multiple large-scale projects exploring biological signatures of (combinations of) external insults and their relationships to health. He is involved in the Real-time Assessment of Community Transmission (REACT) study as lead statistician and contributed to the real-time monitoring of the SARS-CoV-2 epidemic in England. His group includes 20 multidisciplinary scientists focusing on the analysis of data from mega-sized and/or deeply phenotyped studies.

Sébastien Déjean is a Research Engineer at the Institute of Mathematics of Toulouse, and an expert in statistical information. For several years, he has been actively engaged in interdisciplinary research projects that integrate statistics - particularly data analysis - with other scientific domains. His collaborations in the field of biology are primarily oriented towards the analysis and integration of omics data.

Quentin Dufour  is a Junior Professor at the Centre Norbert Elias and Deputy Director of The Institut Santé Numérique en Société (PariSanté Campus). His research project focuses on the political and ethical issues involved in the reuse of health data - a practice widely endorsed by public authorities since the late 2000s. Situated at the intersection of Science and Technology Studies (STS) and Data Studies, the project examines work situations in which groups of actors intervene to make data reusable. The central hypothesis is that such intervention is not purely technical: it involves decisions about the nature of the data, the kinds of knowledge they produce, the uses to which they can be put, and the forms of regulation they may - or may not - comply with. In other words, the ethical and political dimensions of reuse are embedded in the data themselves. The research adopts an ethnographic approach to trace how these issues materialize in data work, what tensions they generate, and how these tensions are handled in practice. Empirically, the project focuses on cases of reuse across several domains: epidemiological cohorts, genomics, and AI models applied to health.

David Hajage is a University Professor and Hospital Practitioner in Biostatistics within the Department of Public Health at Pitié-Salpêtrière Hospital. He is a member of the PEPITES team (Pharmaco-epidemiology and Healthcare Assessment) at the Pierre Louis Institute of Epidemiology and Public Health. IPLesp (Inserm UMR-S 1136) brings together several epidemiology and public health research teams at Sorbonne University. The PEPITES team, one of these 6 teams, focuses on pharmaco-epidemiology (use, misuse and benefit/risk of drugs and medical devices after they have been placed on the market), as well as the evaluation of complex care strategies (e.g. treatment sequences, multimodal interventions, etc.) with a particular interest in several clinical areas and specific populations. More specifically, the main research themes concern people with chronic inflammatory diseases, pregnant women and the elderly. At the same time, the PEPITES team has expertise in management and use of complex healthcare databases, in particular the Système National des Données de Santé (SNDS), as well as in setting up and running large-scale prospective cohort studies, in statistical methods for causal inference in observational situations, and in systematic reviews, metaanalyses and meta-epidemiology.

Sabine Hoffmann is currently Head of the Statistical Consulting Unit (StaBLab) at the Institute of Statistics of the Ludwig-Maximilians-Universität München, a position she has held since October 2024. Prior to that, she served as lecturer and Interim Professor of Biostatistics at the Institute of Statistics. She earned her PhD in Biostatistics in 2017 from the Institut de Radioprotection et de Sûreté Nucléaire (France), focusing on Bayesian hierarchical methods to account for measurement error in low-dose ionizing radiation exposure studies applied to a cohort of uranium miners. Her research focuses on developing statistical methodologies to correct for the impact of measurement error and other sources of uncertainty, especially in routine and observational data, as well as collaborating with applied researchers to improve research reproducibility, open science practices, and methodological rigor.

Florian Naudet is a psychiatrist, meta-researcher and former post-doctoral fellow at METRICS (the Meta-research Innovation Center at Stanford). He's currently Professor of Therapeutics at Rennes University, and a senior member at the Institut Universitaire de France. His research interests are evaluating and developing methodological solutions to assess treatments in patients, primarily but not exclusive in psychiatric research. He has a strong interest in studying research wastes and data-sharing practices.