Pavel Perezhogin
Subgrid parameterizations for ocean models.
I am currently a Postdoctoral Associate at Courant Institute of Mathematical Sciences, New York University, working with Prof. Laure Zanna, and as a part of M2LInES project. I am working on application of Machine Learning (ML) methods (generative ML, physics informed ML, equation discovery) to subgrid parameterizations of ocean mesoscale eddies and their implementation to ocean models.
Previously, I obtained my PhD at Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS) in Moscow, under a supervision of Dr. Andrey Glazunov. My dissertation is devoted to development of stochastic and deterministic parameterizations of kinetic energy backscatter produced by mesoscale eddies with implementation to the NEMO ocean model (In Russian).