Area of research
Atmospheric Science · Statistical and Nonlinear Physics
Research interest
Research interests include Meteorological Phenomena and Simulations, Model Reduction and Neural Networks, Spectroscopy and Quantum Chemical Studies, and Climate variability and models.
Neural general circulation models for weather and climate
Pushing the frontiers in climate modelling and analysis with machine learning
Lagrangian Neural Networks
Learning data-driven discretizations for partial differential equations
Assessing microscope image focus quality with deep learning
xarray: N-D labeled Arrays and Datasets in Python