Hi There!
I am an LSST-DA Catalyst Prize Postdoctoral Fellow and
am currently hosting my fellowship at the University of Washington Astronomy Department
& the DiRAC Institute. I use the latest advances in machine learning in conjunction with
robust statistical techniques and large surveys to derive new insights into the formation and evolution of galaxies. I also dabble in investigating the specific role played
by Active Galactic Nuclei in this process.
New Result: Most recently, we have used a sample of $\sim 3$ million Hyper Suprime-Cam galaxies to demonstrate with $>5\sigma$ confidence that galaxies in denser environments are
upto $\sim 25\%$ larger than their counterparts with similar mass and morphology in less dense regions of the universe. This comprehensive study is
an important step in resolving decades of contradictory results on this topic. It also sheds new light on how the
structure of galaxies is connected with their dark matter halos; as well as their merger history.
ML Frameworks & Catalogs: This above result was made possible in large part by our focus on developing novel
Bayesian machine learning frameworks to determine the structural parameters of
millions of galaxies and AGN. In particular, we have focused on enabling these frameworks to make robust predictions with well-calibrated uncertainties; while necessitating
minimal pre-analyzed training data. We have used these frameworks to produce
one of the largest structural parameter catalogs till date, containing $\sim 8$ million Hyper Suprime-Cam galaxies.
You can find more details about my research as well all publicly available
codes and models at this link. You can
reach me at aritrag (at) uw.edu and aritraghsh09 (at)
gmail.com