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CEST group wins supercomputing Grand Challenge

Researchers from the CEST group have successfully applied for a special supercomputing assignment to carry out research related to climate change.
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Supercomputer Mahti, BullSequana XH2000 from Atos. Image: CSC 2020.

CEST group researchers from the Department of Applied Physics were awarded a competitive Grand Challenge project on Finland鈥檚 biggest supercomputer Mahti to explore 鈥淎ctive machine learning methods for atmospheric science applications鈥.

Milica Todorovi膰 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 Kurt茅n and Prof. Hanna Vehkam盲ki 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.

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