Home University: University of Harvard
Petros Koumoutsakos has a wide research spectrum in applied mathematics, ranging from scientific computing over numerics and machine learning. His application spectrum is equally wide – he is especially prolific in numerical fluid mechanics, but also works on molecular dynamics and other topics. He will be easily able to integrate in the CRC. Collaboration is in particular foreseen with projects A04 and B08 in the context of Machine Learning, Bayesian Model selection and specifically on annealed importance sampling which is closely related to the Stochastic Normalizing Flows involved in B08. C01 will take advantage of Petros Koumoutsakos’ expertise on the particle-continuum coupling for the refinement and application of the AdResS-continuum scheme.