Conference, Workshop and Seminar Organization 

AI Meets Stars: Advancing Our Understanding of Stellar Lives and Fates with Machine Learning 

Where and when? 247th meeting of the  American Astronomical Society, Phoenix, Arizona, 5 January 2026

Stellar evolution lies at the heart of many fundamental questions in astrophysics, from the formation of compact objects to the enrichment of galaxies with heavy elements. While decades of theoretical modelling and observational breakthroughs have shaped our current understanding, the increasing complexity and computational demands of stellar modelling could benefit from innovative approaches.  

This special session held as part of the 247th AAS meeting aims to explore how how machine learning can transform the way we model, interpret, and predict stellar birth, evolution and afterlife.  

AstroNuc 2026 - Nuclear Astrophysics Workshop: Nucleosynthesis from Stars to Galaxies

Where and when?  March 10-13, 2026, The University of Arizona, Tucson, Arizona, USA. 

JWST and LSST have begun releasing remarkable new data on transients, making an understanding of the nuclear processes in their final stages essential for accurate interpretation. Complementing these efforts, SDSS-V is delivering all-sky spectroscopic observations that provide critical insights into chemical enrichment and evolution. In the coming years, gravitational-wave detections of compact object mergers with LVK and Cosmic Explorer are expected to shed light on the formation of heavy elements and the rate of key nuclear reactions in stars, which will be further constrained in new laboratory measurements. At the same time, the growing use of machine learning in both data analysis and simulations, which is manifested in new institutes like SkAI and CosmicAI, and a growing number of publications, is opening new avenues for nuclear astrophysics research. Together, these recent and anticipated advances are transforming our ability to study nucleosynthesis in stars and stellar explosions.

AstroNuc 2026 will bring together observers, theorists and experimentalists working in nuclear astrophysics. Our goal is to discuss advancements in stellar and explosive nucleosynthesis, including their role in chemical enrichment of galaxies, leveraging insights from recent time domain astronomy initiatives and new machine learning approaches.