Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data
Fine-grain morphological classifications at astronomical scale.
I work on the research, development, and application of machine learning and optimization techniques to challenging scientific problems.
Working at the intersection of computer science, statistics, and domain science, I work other researchers to develop new methods and tools to solve complex problems. I work at the Institute for Data Intensive Engineering and Science at the Johns Hopkins University. I am also a member of the JWST Advanced Deep Extragalactic Survey (JADES) collaboration working to unlock the secrets of the early universe using the James Webb Space Telescope.
Research Projects
FitsMap
A tool for displaying astronomical images and their associated catalogs.
Morpheus Core
The core framework code to scale up per-pixel machine learning methods to large astronomical images.
Partial-Attribution Instance Segmentation for Astronomical Source Detection and Deblending
A new technique for the detection and deblending of astronomical sources using deep learning.