Machine Learning in Sustainable Energy Systems

Who we are: We’re the MLSES group within the Cluster of Excellence – Machine Learning for Science at the University of Tübingen and are interested in developing new machine learning algorithms to build and maintain a future sustainable energy system.

Team

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Nicole Ludwig

Research Group Leader

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Florian Ebmeier

PhD Student

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Gwen Hirsch

PhD Student

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Kibidi Neocosmos

PhD Student

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Kornelius Raeth

PhD Student

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Nina Effenberger

PhD Student

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Mara Seyfert

MSc Student

Research Areas

Climate Change Impacts on Energy Systems
How does climate change impact a renewable energy system?
Climate Change Impacts on Energy Systems
Sustainable ML
How can we assess and improve the sustainability of machine learning models?
Probabilistic Forecasting
How can we reliably predict time series in complex systems under uncertainty?
Probabilistic Forecasting
Statistical, Physical Information and Modularity
How can we include statistical information such as seasonality, trends or concept drifts into DNNs to improve forecasting?
Statistical, Physical Information and Modularity
Demand Side Flexibility & Markets
How can we recognise, promote and use flexibility on the demand side?
Demand Side Flexibility & Markets
FEAT
BMBF funded research project: Machine Learning in Complex Systems under Uncertainty
FEAT

Where to find us

  • Maria-von-Linden Str 6
    72076 Tübingen