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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Kibidi Neocosmos

PhD Student

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Nina Effenberger

PhD Student

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Gwen Hirsch

MSc Student

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Ludwig Bald

MSc Student

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Ricarda Hogl

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
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

Where to find us

  • Maria-von-Linden Str 6
    72076 Tübingen