معرفی
Aritra Ghosh is a Research Fellow and Postdoctoral Scholar at the University of Washington Astronomy Department and the DiRAC Institute, supported by the LSST-DA Catalyst Prize Fellowship and UW Data-Science Fellowship. His research focuses on leveraging machine learning and large astronomical surveys to study galaxy formation, evolution, and the role of AGN. He holds a Ph.D. in Astrophysics from Yale University (2023), an M.Sc. in Physics from the University of Groningen (2017), and a B.Sc. in Physics from Presidency University, Kolkata (2015).
He has conducted research in computational astrophysics during his undergraduate summers and pursued graduate studies in both Europe and the U.S. His current work includes analyzing ∼3 million Hyper Suprime-Cam galaxies to demonstrate with >5σ confidence that galaxies in dense environments are up to 25% larger than those in less dense regions. This work connects galaxy structure with dark matter halos and merger histories, resolving decades of conflicting results. The findings were featured in space.com and phys.org.
Research interests include developing bespoke machine learning tools for astrophysical applications, such as uncertainty-calibrated CNN frameworks for galaxy morphology catalogs. These tools have enabled novel insights into AGN-host galaxy interactions and cosmological processes. Collaborations span UW e-Science Institute and Meg Urry's group at Yale. For personal projects and further details, visit his website.
