Pavel Perezhogin
Subgrid parameterizations for ocean models.
I am currently a Research Scientist at Courant Institute of Mathematical Sciences, New York University, working with Prof. Laure Zanna, and Lead Scientist in 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. My current interest is the application of calibration methods for climate modeling.
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).