Title: What a machine sees? - Galaxy morphological classification told through machine learning
Speaker: Dr. Ting-Yun (Sunny) Cheng (Durham University)
Date: February 26 at 14:30
Location: R521, General Building II
Abstract:
Along with the significant development of astronomical data in 4V aspects (Volume, Velocity, Variety, and Value/Veracity), machine learning techniques, as an analysis tool, are applied in a broad range of astronomical studies. In my PhD, I studied galaxy morphology with supervised and unsupervised machine learning techniques for two types of tasks - classification and exploration. In this talk, I will give an overview about how I think machine learning techniques can be used in astronomical studies, in particular, galaxy morphological classification, with four projects I accomplished during my PhD using a broad range of data (DES, SDSS, simulated data for Euclid). Additionally, I would like to bring up a discussion about a possibility of a new astronomical approach may be carried out through machine’s perspective.
