COLLOQUIUM 2024
Transcending the Limits of Theoretical Astrophysics with Deep Learning
| Speaker | Ting Yuan Sen, Australian National University |
| Date/Time | Wednesday, 7 February, 2PM |
| Location | Conference room: S11-02-07 |
| Host | Prof Gong Jiangbin |
Abstract
Astronomy has recently experienced a profound transformation, driven by the acquisition of extensive datasets generated by increasingly sophisticated instruments. This influx of data has opened up numerous new avenues for exploration in the field. However, this boon is accompanied by its own set of challenges, as astronomical phenomena often exhibit intricate and are inherently high-dimensional. These complexities involve precise imaging, spectral analysis, and time series data.
Traditional statistical methods in astronomy can struggle to effectively handle these complexities. Deep learning offers a solution by effectively addressing the challenges by allowing for a more faithful representation of the intricate astronomical phenomena. In this talk, I will delve into deep learning approaches for characterizing complex astronomical systems. Additionally, it will explore the theoretical underpinnings of deep learning, including its close relationship with symmetry and physics. This exploration will encompass a diverse range of applications in astronomy, including asteroseismology, stellar spectroscopy, weak lensing, reionization, galactic dynamics, galaxy evolution, and quasars. These applications collectively contribute to expanding the boundaries of Bayesian statistics and theoretical astrophysics, all within the framework of deep learning.
Biography
Yuan-Sen is an Associate Professor in astronomy and computer science at the Australian National University and the Ohio State University. Yuan-Sen’s research applies machine learning to advance statistical inferences using large astronomical survey data. A Malaysian native, Yuan-Sen received his PhD in astronomy and astrophysics from Harvard University in 2017. After graduating, Yuan Sen was awarded a unique four-way joint postdoctoral fellowship from Princeton University, Carnegie Institute for Sciences, NASA Hubble and the Institute for Advanced Study at Princeton before reallocating to Australia. Yuan-Sen also serves as the co-chair of the NASA Cosmic Programs Stars Science Interest Group and leads future spectroscopic surveys as the science group leader. He is an author of more than 180 journal articles, many of them on topics at the frontier of astrophysics and machine learning.