Vincent Garot

I am interested in understanding virus epidemics using genomic data. For this, I develop Machine Learning methods, involving transformers to analyze sequence data, which open many potentialities compared to conventional approaches. Two of the advantages are that the range of models is wider and, once learning is done, parameter estimation is much faster than common Bayesian methods. This is particularly useful for surveillance in the context of emerging infectious diseases. My work is supported by a DIM One HEALTH PhD fellowship.