Rodolphe Thiébaut

Rodolphe Thiébaut is a Professor of Public Health at the University of Bordeaux, specializing in biostatistics and medical informatics. He holds dual roles as head of the medical information department at Bordeaux University Hospital and director of the Inserm/Inria SISTM research team (Statistics for Translational Medicine). He also leads the University School of Digital Public Health Research and the Master's in Public Health Data Science, demonstrating strong academic and institutional leadership in digital health and data-driven medicine.

His research focuses on the statistical modeling of large-scale biological and clinical data to advance translational medicine, particularly in immunology and infectious diseases. Key areas include vaccine development, treatment evaluation, immune response modeling, and epidemic forecasting. His work integrates artificial intelligence, data science, and public health to improve patient care and pandemic preparedness.

The recent publications highlight a strong trend in applying advanced biostatistical methods to vaccine research (Ebola, HIV, SARS-CoV-2), immunological marker analysis, and clinical data integration for epidemic prediction. His work bridges clinical trials, cohort studies, and real-world data, emphasizing mechanistic understanding and predictive modeling in infectious disease dynamics.

• Involved in major EU-funded initiatives like the European HIV Vaccine Alliance (EHVA) with a €28 million budget.
• Contributed to national and international responses during the Covid-19 pandemic through modeling and data analysis.
• Active in promoting ethical AI and secure data sharing frameworks in healthcare.

Rodolphe Thiébaut has advised numerous research projects and supervised students through his leadership in the Master’s program and research team, though specific names are not listed. He has secured significant funding through collaborative grants, particularly in vaccine research and digital health infrastructure. His work emphasizes the integration of clinical data warehouses, AI tools, and secure data governance to support public health decision-making.

He leads the SISTM research group, a joint Inserm/Inria team focused on statistical methods for translational medicine. This team develops models for vaccine efficacy, immune response dynamics, and epidemic forecasting. The group collaborates with European and international partners in infectious disease research and is embedded in both academic and hospital ecosystems, enabling rapid translation of research into practice.