My research interests include pattern recognition, topological data analysis, machine learning (including deep learning), dynamical systems, and climate science.
In particular, I develop and apply topological methods and machine learning techniques for detecting extreme weather events (patterns), e.g. Atmospheric Rivers and Atmospheric Blocks.
You can find more details on Dr. Vitaliy Kurlin's blog and popular articles: NERSC Science News, (July 2019), HPC Wire, (December 2018), HPC Wire, (September 2018), the University's news, (2017).
I participate in ARTMIP -- Atmospheric River Tracking Method Intercomparison Project.