Astronomy and astrophysics are undergoing a rapid evolution towards data-driven science. Large-scale astronomical surveys and computer simulations are creating enormous amounts of datasets that require the development of new techniques for their analysis. Both complexity and sheer size of these datasets, and often the necessity of combining heterogenous sources of data, put machine learning methods as a central tool, present and future, for scientific discovery in astronomy.

The program of the 4th Institute of Space Science Summer School will focus on artificial intelligence (AI) methods for astronomy research, with special focus on neural networks for image classification, natural language processing and graph neural networks. The topics will cover the mathematical concepts as well as the development of software tools and applications. There will be lectures and hands-on activities.

The Institute of Space Sciences will welcome around 40 Master and Doctoral students to the Summer School in which they will broaden their knowledge on this exciting field as well as getting into contact with research groups working at the Institute in this and other fields. Applications from young postdocs are also welcome.