I work on the application and integration of machine learning (ML) in Earth System Modelling (ESM). This research has started with the development and training of neural networks for specific tasks, e.g., the inversion of Earth system observations to estimate geophysical quantities. Further ML applications were developed in the topics of data assimilation and physical downscaling. Now, I increasingly focus on a generalized development of self-validating, physically consistent, and interpretable hybrids of neural networks and our available Earth system models (Fusion of ML and ESM).
This work includes a diverse range of research questions, e.g.:
Our work in public media
CarbonBrief Guest Post: How AI is fast becoming a key tool for climate science
Opportunities and limits of AI in climate modelling
Artificial Intelligence learns continental hydrology
Artificial intelligence and data assimilation: A successful marriage for Earth system research
An artificial neural network for monitoring ocean warming
Since July 2017: PostDoc in section 1.3 "Earth System Modelling"
2014 - 2017: PhD student in the Helmholtz graduate school GeoSim, Freie Universität Berlin (PhD Thesis)
2010 - 2013: M.Sc. Mathematics at Christian-Albrechts-Universität zu Kiel
2007 - 2010: B.Sc. Mathematics at Philipps-Universität in Marburg