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 choosing the right data is at least as crucial as choosing the right model.
During my PhD I have also conducted a half-year research stay with the Weather Forecast Research Team at the University of British Columbia in Vancouver, Canada.
Additionally, I am trained in mental health first aid and promote mental health in academia. I am also part of the PhD initiative sustainAbility.
news
| Nov 19, 2024 | Our pre-print Climate data selection for multi-decadal wind power forecasts is now available on arxiv. |
|---|---|
| Oct 25, 2024 | Our pre-print Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6 is now available on arxiv. |
| Oct 17, 2024 | Towards turbine-location-aware multi-decadal wind power predictions with CMIP6 has been chosen for a spotlight presentation at CCAI’s Tackling Climate Change with Machine Learning workshop at NeurIPS 2024. |
| Aug 28, 2024 | Our pre-print Towards turbine-location-aware multi-decadal wind power predictions with CMIP6 is now available on arxiv. |
| Aug 12, 2024 | Our article got published in the DFG journal forschung (in German). |