I’m a theoretical physicist mainly interested in climate data analysis using probabilistic models.
- Climate data analysis (i.e. spatial-temporal data from satellites and meteorology)
- El Nino Southern Oscillation prediction and diversity
- Interaction between climate systems
- Uncertainty quantification
- Probabilistic models (Gaussian process regression, Bayesian NN)
- Generative models (Hidden Markov models, Variational Autoencoders)
- Nonlinear data analysis (complex networks, kernel methods)
I obtained my Bachelor in Physics at the University of Konstanz which was followed by a Masters in Physics at the University of Regensburg. During my studies I spent five months at the Weizmann Institute of Science in Israel and half a year at Bosch Research in Renningen. Since September 2020, I’m a PhD student in the Machine Learning for Climate Science group at the University of Tübingen and I’m part of the International Max-Planck Research School for Intelligent Systems. Privately, I love sports, nature and wildlife.