My research focuses on the mathematical and computational aspects of statistical mechanics, with applications to complex dynamical systems arising in molecular dynamics, materials science, atmosphere-ocean science, fluids dynamics, and neural networks. More recently I have become interested in the mathematical foundations of machine learning (ML) and started to explore the exciting new prospects ML offer for scientific computing. My work combines tools from probability theory, mathematical physics, numerical analysis, and optimization to uncover governing principles in complex systems and design efficient algorithms for their simulation.