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CEST group researchers from the Department of Applied Physics were awarded a competitive Grand Challenge project on Finland’s biggest supercomputer Mahti to explore “Active machine learning methods for atmospheric science applications”.

Milica Todorović and Patrick Rinke will manage a 15 million core-hours project, awarded to advance cutting-edge research with large computational needs, in cross-disciplinary collaboration with the groups of Dr. Theo Kurtén and Prof. Hanna Vehkamäki at University of Helsinki.

Active learning dataset curation techniques, developed by Kunal Ghosh at CEST, will be employed to optimize the quality of machine learning of aerosol condensation properties for small atmospheric molecules. This is important information for atmospheric climate models that shape public policy on climate change.