Forschung

Die Forschung innerhalb von JARA CSD integriert neuartige Methoden der Simulations- und Datenwissenschaften. Das beinhaltet innovative Methoden zur Lösung nichtlinearer partieller Differentialgleichungen, kontinuierliche und diskrete Optimierung, maschinelles Lernens, physikalisch inspirierte Datenwissenschaft und Hochleistungsrechnen. Unsere Projekte sind anwendungsorientiert und konzentrieren sich auf gesellschaftliche Herausforderungen wie Energiekrise, personalisierte Medizin, Umwelt und globalen Klimawandel.

ERS Prep Fund Projects in JARA CSD

Towards an integrated data science of complex natural systems

Beteiligte JARA CSD-Mitglieder: Martin Grohe, Moritz Helias, Abigail Morrison, Holger Rauhut, Michael Schaub

Abstract: Quantitative natural sciences have a long, successful history of obtaining insights into nature by applying a reductionist, model-driven approach to explain empirical observations from a small set of principles. Identifying these principles is the very objective of science, and our ability to comprehend and ultimately control our world critically hinges on this deep understanding of nature.

Project presentation during the JARA CSD Workshop in August 2022

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Deep Image Data Analysis for Precision Medical Imaging

Beteiligte JARA CSD-Mitglieder: Volkmar Schulz

Abstract: Modern medical imaging devices generate an ever-increasing data volume of surging information
granularity. In order to cope with this high data volume, the acquired raw data are currently heavily
filtered and compressed using classical, historically developed signal processing techniques.

Project presentation during the JARA CSD Workshop in August 2022

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High Performance Computing in the Geosciences

Beteiligte JARA CSD-Mitglieder: Harrie-Jan Hendricks-Franssen, Harry Vereecken, Florian Wellmann

Abstract: Geoscientific studies have a major global economic and societal impact: They are fundamental
to understanding the physical, chemical, biogeochemical and biological processes of the Earth,
in order to develop forecasts, and derive strategies for action – and this aspect is also evident in
the fact that modeling of Earth and Environment is identified as one of the “Grand Challenge
Problems” in the House of Simulation and Data Science of JARA-CSD. Although geoscientific
investigations are extremely diverse, they share cross-sectional methodologies, as uncertainty
quantification and data assimilation. Due to the computationally demanding nature of these crosssectional
methodologies, High-Performance Computing (HPC) is of significant importance.

Project presentation during the JARA CSD Workshop in August 2022

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Weitere Forschungsprojekte