Tom Beucler is an assistant professor of environmental data science at the University of Lausanne in Switzerland. He recently started a lab specifically dedicated to the intersection of atmospherics physics and machine learning, with the goal of improving our understanding of atmospheric dynamics and assisting weather and climate predictions. For that purpose, his research group combines physical theory, computational science, statistics, numerical simulations, and observational analyses. Before that, Tom studied the interaction of tropical storms, radiation, and atmospheric water as part of his PhD at MIT. As a postdoc and project scientist at Columbia and UC Irvine, he investigated how to best integrate physical knowledge into neural-network representations of convection for climate modeling, which will be the theme of today’s presentation.