Moonzarin is a second year astronomy graduate student. She works with Yuanyuan Zhang and Louis Strigari on constraining the fundamental cosmological parameters using novel machine learning techniques. She is interested in using data from cosmic surveys to determine the role of dark matter in galaxy formation and evolution. In the past, she has worked on morphological classification of galaxies and photometric redshift estimation using various machine learning algorithms. She received her BSc in EEE from Bangladesh University of Engineering and Technology in 2019.


Research Team

Institutional Partnerships

Research Areas

  • Dark Matter Theory
  • Data-Intensive Computation
  • Galaxy Evolution