Machine Learning application for astrophysics: A case study for black hole images and strong gravitational lensing

Modern astronomy research has been thriving due to new observations. To handle large and novel datasets, deep learning tools for computer vision (e.g. Convolutional Neural Networks and Vision Transformers) provide a new way to tackle the challenges in data analysis. In this talk, I will cover some of the recent development of deep learning on several astrophysics projects including supermassive black holes (SMBH), and strong gravitational lensing.