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- Seminars and Workshops
- Institute of Astronomy and Astrophysics
- Location
R1203 of the Astronomy-Mathematics Building, National Taiwan University
- Speaker Name
Ting-Yun Cheng (Sunny) (Durham University)
- State
Definitive
- Url
What a machine sees? - Galaxy morphological classification told through machine learning
2021-01-20 14:00 - 15:30
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.
