Machine learning and AI in Astrophysics

Professor: Tuan Do

Description: Our lab seeks to use machine learning methods to enable discoveries in astronomical data. The scale and complexity of astronomical data are growing exponentially, so it is important that our tools and methods grow as well to enable new discoveries. Our group studies both how machine learning is being used in astronomy and applies machine learning methods to challenging astronomical problems such as the nature of dark matter and dark energy. Potential projects include integrating more physics information into neural networks and using explainable AI methods to gain insight into how and why machine learning models work in astrophysical context.

Preferred Qualifications: Some Python programming skills, linear algebra