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 applying Machine Learning (ML) techniques, including generative ML, physics-informed ML, and equation-discovery models, to the parameterization of ocean mesoscale eddies, with a focus on their implementation in the global 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).