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.
news
| Aug 28, 2024 | Our pre-print Towards turbine-location-aware multi-decadal wind power predictions with CMIP6 is now available on arxiv. |
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| Aug 12, 2024 | Our article got published in the DFG journal forschung (in German). |
| 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. |
selected publications
- Mind the (spectral) gap: how the temporal resolution of wind data affects multi-decadal wind power forecastsEnvironmental Research Letters, 2024