Nina Effenberger

PhD student at the University of Tübingen.


Since July 2021 I am a PhD student in the research group Machine Learning in Sustainable Energy Systems within the Cluster of Excellence – Machine Learning for Science at the University of Tübingen. Furthermore, I am part of the International Max Planck Research School for Intelligent Systems (IMPRS-IS).

My current research focuses on developing probabilistic machine learning algorithms for wind power forecasting. I am very interested in physics-informed machine learning and believe that chosing the right data is at least as crucial as choosing the right model.

During my PhD I have also conducted a research stay with the Weather Forecast Research Team at the University of British Columbia in Vancouver, Canada.

Additionally, I promote mental health in academia and I am also part of the PhD initiative sustainAbility.


Jul 19, 2024 I recently talked to Shannon Hall about well-being in academia. How PhD students and other academics are fighting the mental-health crisis in science is now published in Nature’s News Feature.
Jul 02, 2024 Our abstract got accepted at INREC 2024.
Jun 05, 2024 I will give a talk at ProbNum 24 in London, on 15 July.
Apr 07, 2024 I will present my work at the BDEW science corner in Berlin, on 05 June.
Feb 13, 2024 Our abstract Probabilistic Wind Speed Downscaling for Future Wind Power Assessment got accepted at EGU.

selected publications

  1. Mind the (spectral) gap: how the temporal resolution of wind data affects multi-decadal wind power forecasts
    Nina Effenberger, Nicole Ludwig, and Rachel H White
    Environmental Research Letters, 2024