Research

Statistical optimal transport: development of estimators based on optimal or approximate versions (e.g. entropic optimal transport, rectified transport) of the transport problem and study of their theoretical properties (e.g. rates of convergence). Applications to robust statistics, (high-dimensional) clustering, etc.
Development of models for conceptualizing pathology progression and their inference from cohorts of donors in Alzheimer’s Disease, and the study of the fundamental inferential limits of these models. In collaboration with the SEA-AD
Meta-analysis, epidemiology: development methods for combining heterogeneous sources of data (such as biased and unbiased data) and the study of their statistical properties (e.g. risk analyses). Applications to COVID-19 epidemiology.
Growing interest in genomics, spatial transcriptomics.

I am seeking collaborations with students. Please reach out to me if you are a motivated student interested in working in any of the above problems