YEAR 4 NSF SITE VISIT: STUDENTS + POSTDOCS
Matthieu Blanke || Postdoc, NYU
Areas of Study: Applied Mathematics and Deep Learning Methods for Climate
Advisors: Sara Shamekh, Pierre Gentine
We are developing deep generative models for climate systems, constrained by the law of physics. The targeted applications are parameterization for the boundary layer in climate models and data assimilation.
Francesco Immorlano || Postdoc, UC Irvine
Area of Study: Use of Generative Models for Climate Science
Advisors: Stephan Mandt, Pierre Gentine
Application of generative models to provide estimates of future global warming with uncertainty quantification. Application of generative models to downscaling of Global Climate Models.
Joseph Ko || Postdoc, Columbia University
Area of Study: Ice Cloud Microphysics
Advisors: Kara Lamb, Marcus van Lier-Walqui
(1) Constraining ice microphysical properties from in situ observations using machine learning.
(2) Using a hierarchy of numerical models (from LES to climate models) along with data-driven methods to constrain parametric and structural uncertainties in cirrus cloud processes.
Aya Lahlou || Graduate Research Assistant, Columbia University
Area of Study: Phenology
Advisor: Pierre Gentine
Aya is interested in using deep learning methods and GIS data to uncover underlying patterns of climate change. She is currently studying the effects of climate change on leaf-out phenology and leaf senescence patterns
Kaitlyn Loftus || Postdoc, Columbia University
Area of Study: Atmospheric and Oceanic Sciences
Advisors: Marcus van Lier-Walqui, Hugh Morrison
I am working on liquid cloud microphysics parameterizations, and am broadly interested in how hydrological cycles work on different planetary bodies (e.g., modern Earth, ancient Mars, Titan, exoplanets).
Tony Manriquez || LEAP REU 2024 Student
Area of Study: Atmospheric and Oceanic Sciences
Advisor: Dhruv Balwada
Using high resolution atmosphere-ocean couple models, research over the last two decades has highlighted the significance of heterogeneity in the air-sea exchange, and the impact this has on the boundary layers, surface flows, winds, clouds and rainfall. Given a low-resolution (LR) or smooth map of sea surface height (SSH, as may be observed with satellites), we are trying to reconstruct the higher resolution (HR) map of SSH using Machine Learning (ML).
Racheet Matai || Postdoc, Columbia University
Area of Study: Ice Sheet Modeling
Advisor: Jonathan Kingslake, David Porter
Accurately modeling ice flow is hindered by the challenge of representing basal conditions, typically estimated through numerical inversions using satellite-derived data. This project proposes a novel framework leveraging local topographical, geophysical, and ice feature data to predict basal friction and identify which local features best inform such models.
Kyle McEvoy || LEAP Momentum Fellow 2024; PhD student (UCLA)
Area of Study: Statistics
Advisor: Karen McKinnon (UCLA)
Broadly, my research is on applications of Statistics to Climate Science with a focus on understanding and quantifying the internal variability of the climate system. My current work is on estimating uncertainty in North American precipitation extremes.
Yongquan Qu || Graduate Research Assistant, Columbia University
Areas of Study: Machine Learning for Turbulence and Data Assimilation
Advisor: Pierre Gentine
My research centers on developing machine learning–based parameterizations for low-cloud turbulence and designing new data assimilation algorithms that incorporate machine learning. I leverage high-resolution simulations, differentiable physical models, scientific ML approaches, and generative models to improve the accuracy and efficiency of Earth system predictions.
Christina Torres || Graduate Research Assistant, Teachers College-Columbia University
Area of Study: Climate Change Education, Science Education
Advisor: Ann Rivet, Oren Pizmony-Levy
I study climate education, broadly speaking. I research science identity and science learning within youth climate groups in NYC as part of my dissertation research. At LEAP, I help run a Summer Institute to train NYC Public School teachers to integrate climate into their curriculum and pedagogy cross-discipline.
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