Enhancing computational astrophysics with interpretable machine learning

Focus topic:	Artificial Intelligence
Type of funding:	Individual funding programmes
Programme:	CZS Nexus
Funded institution:	Universität Heidelberg

Tobias Buck holds a doctorate in astrophysics. During his studies at the University of Heidelberg, he focused on robotics, machine learning and space exploration. Most recently, he worked as a postdoc at the Leibniz Institute for Astrophysics in Potsdam.

Goals

The aim of the research project is to develop innovative computational methods from the synthesis of physical laws and machine learning.

In an international, interdisciplinary team of scientists, modern machine learning methods are combined with high-resolution computer simulations to gain new scientific insights into the formation of galaxies.

With his research group at the Interdisciplinary Centre for Scientific
Computing and the Centre for Astronomy in Heidelberg, Dr. Tobias Buck would like to advance astrophysics and make machine learning algorithms more robust and interpretable.