Mihai Bărbosu
Rochester Institute of Technology, Rochester NY, USA

Mathematical models are fundamental to the design and implementation of Machine Learning (ML) and Artificial Intelligence (AI) techniques. These models provide formal representations of the problems and guide the performance of adapted algorithms. ML and AI have emerged as powerful tools in the field of astronomy and have proven to be instrumental in automating the analysis of vast amounts of astronomical data, allowing astronomers to process and extract meaningful information efficiently. This paper explores several AI methods that have revolutionized the way we classify and discover new celestial objects, study astronomical images, light curves, transient events in the universe, or the approach we take in optimizing astronomical instruments. Moreover, the integration of AI into celestial mechanics enhanced our understanding of the dynamics of celestial objects, enabling more accurate orbit predictions and efficient mission planning, empowering spacecraft to navigate with minimal human intervention.