NEMESIS is an EU Horizon 2020/SPACE-funded project from March 2021 to February 2025. It was a collaboration between the Department of Astrophysics at University of Vienna, the University of Geneva, and the Konkoly Observatory. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101004141.

NEMESIS had the ambition to reshape our understanding on the formation of stars by employing artificial intelligence methods to interpret the largest, panchromatic data collection of young stellar objects. To meet these goals NEMESIS compiled large, panchromatic datasets of young stellar objects in nearby star-forming regions, harnessing critical information that resides in data from space missions. It reprocessed and analyzed this unique dataset with supervised and unsupervised machine learning algorithms, deep learning neural networks for object detection, clustering and regression analysis of images in order to advance the analysis and interpretation beyond the current state-of-the-art. Ultimately, NEMESIS brought big data techniques and hybrid machine learning methods to systematically analyze and interpret large data volumes in order to answer some of the most persisting questions, paving the path toward data intensive science applications in modern astrophysics.

For more details: please look at https://nemesis.konkoly.hu