Utilized deep learning to solve inverse solar physics problem. Training models on over 100TB of simulation data. Model to be deployed in Daniel K. Inouye Solar Telescope workflow.
Used self-supervised representation learning to train a foundation model for SAR WV mode. Applied model to retrospectively analyze 9 years of global-coverage data.
Consolidated multiple longitudinal NIH studies with different imaging views to train a self-supervised DXA vision model and derived a multi-modal mortality marker based on body composition information in tabular fitness markers.
Designed neural network architecture based on known physics principles for Belle II detector Kaon/ Pion particle identification.