I am a Ph.D. candidate at Yale University. I use the latest advances in machine learning
combined with large surveys to study the formation & evolution of galaxies, and investigate the specific role played
by Active Galactic Nuclei in this process.
Most recently, I have been developing Bayesian machine learning frameworks to extract morphological
parameters (e.g., radius, bulge-to-total light ratio) of galaxies & AGN. I have focused on enabling these frameworks
to predict uncertainties which are well callibrated and accurate. I have used these to produce brand-new morphological catalogs for $\sim 8$ Million
Hyper Suprime-Cam galaxies. We have used these catalogs to identify and investigate different evolutionary pathways for
galaxies & AGN with varying morphologies.
You can find more extensive details about my research here. You can
reach me at
aritra.ghosh (at) yale.edu and