Hervé Cardot

Hervé Cardot is a Professor of Statistics and team leader of the Statistics, Probability, Optimization and Control (SPOC) group at the Institut de Mathématiques de Bourgogne (IMB), University of Burgundy. His research spans functional data analysis, stochastic algorithms for robust estimation, survey sampling methodology, and applied statistics across diverse fields.

• Research Interests: Functional data analysis, online principal component analysis, zero-inflated regression, survey sampling, nonparametric estimation
• Key Applications: Agriculture, climatology, energy consumption, food science, remote sensing, medical imaging

Recent Work includes:

• Developing statistical frameworks for analyzing categorical trajectories using multivariate functional PCA (2025)
• Advancing bias-robust estimation for functional data in survey sampling (2020)
• Creating online stochastic algorithms for high-dimensional robust estimation (2017)
• Applying semi-Markov models to sensory analysis (2018)

Teaching at the University of Burgundy includes courses on statistical modeling, big data analysis, and applied statistics for economics and psychology. He supervises PhD students in statistics and co-edits Statistics and Probability Letters.