Process management and data analysis in the context of water and energy infrastructure

Research in solving hydrogeological problems with machine learning approaches, including: forecasting, early warning, regionalization, climate impact modeling, coupling physics with deep learning models, sensor network optimization

Forecasting groundwater levels with artificial neural networks based on short-, mid- and long-term weather and climate forecasts/projections, intense research on time series clustering and analysis (MENTOR project)Modelling of groundwater contaminants such as nitrate as part of the NiMo 4.0 project together with TZW, Fraunhofer IOSB and Disy.Innovative machine learning applications in hydrogeology such as modeling karst springs using spatially distributed input data (KARMA… Show more Forecasting groundwater levels with artificial neural networks based on short-, mid- and long-term weather and climate forecasts/projections, intense research on time series clustering and analysis (MENTOR project)Modelling of groundwater contaminants such as nitrate as part of the NiMo 4.0 project together with TZW, Fraunhofer IOSB and Disy.Innovative machine learning applications in hydrogeology such as modeling karst springs using spatially distributed input data (KARMA project) with international partners or using graphs to model spatial relations (KI-GRUMO project).Samples of my work are hosted on Github (linked below). Show less

Collaboration on time series forecasting with artificial neural networks.

Visualization and interpretation of geochemical analysis data, geothermometry and data research. Automation and plausibilization of such analyses with Visual Basic for Applications (VBA) in Excel.

Sampling and preparation of sediment samples for sedimentological and geochemical analyses.

Geological field work (ground surveys, groundwater sampling) and assistance with expert reports (graphics, groundwater contour maps, drilling profiles, etc.).