I am the leader of the early career research group “Machine Learning in Sustainable Energy Systems” within the Cluster of Excellence – Machine Learning for Science at the University of Tübingen.

My research focuses on developing machine learning algorithms for problems related to future sustainable energy systems with a high share of renewable energy sources. I am especially interested in probabilistic machine learning for time series, as well as reinforcement learning with uncertain inputs.

Download my CV.

Interests

  • Probabilistic Machine Learning
  • Machine Learning for Energy Systems
  • (Probabilistic) Time Series Forecasting
  • Reinforcement Learning under Uncertainty

Education

  • PhD in Informatics, 2020

    Karlsruhe Institute of Technology

  • MSc in Information Systems and Network Economics, 2016

    University of Freiburg

  • BSc in Economics, 2014

    University of Freiburg

Recent Publications

Evaluating Ensemble Post-Processing for Wind Power Forecasts
Data analytics in the electricity sector -- A quantitative and qualitative literature review
Forecasting energy time series with profile neural networks
A Method for Sizing Centralised Energy Storage Systems Using Standard Patterns

Experience

 
 
 
 
 

Early Career Research Group Leader

Machine Learning Cluster of Excellence, University of Tübingen

Nov 2020 – Present Tübingen, Germany
 
 
 
 
 

Interim Research Group Leader, PostDoc

HelmholtzAI, Karlsruhe Institute of Technology

Jul 2020 – Oct 2020 Karlsruhe, Germany
 
 
 
 
 

Research Assistant

Institute for Automation and Applied Informatics, KIT

Jun 2019 – Jun 2020 Karlsruhe, Germany
 
 
 
 
 

Visiting Researcher

Mathematical Institute, University of Oxford

Feb 2019 – May 2019 Oxford, UK
 
 
 
 
 

DFG Graduate Student

DFG Research Training Group Energystatusdata, KIT

Jun 2016 – May 2019 Karlsruhe, Germany

Contact