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Ralf Loritz

Ralf Loritz

Ralf Loritz leads the junior research group Energy and Information Flows in Hydrological Systems at the Karlsruhe Institute of Technology (KIT). His group investigates how machine learning and process-based models can be combined to better understand and predict the movement of water through landscapes. He is the principal investigator of the DFG-funded project DETOX (Demystifying Recurrent Neural Networks in a Hydrology Context), which analyzes how well deep learning models can extrapolate to extreme hydrological states, and coordinates the BMBF project KI-HopE, developing AI-based flood and drought forecasting systems for Germany in collaboration with the German Weather Service and several state agencies. His work sits at the intersection of data-driven modeling, hydrological theory, and environmental decision-making. He is particularly interested in what current deep learning models can; and (currently) cannot; learn about the water cycle, and how this understanding can guide the design of more reliable forecasting systems in the future.

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  • Organization
    Karlsruhe Institute of Technology
  • Profession
    Junior Research Group Leader

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