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 diversity
- Generative models (Hidden Markov models, Variational Autoencoders)
- Representational learning
- Physics-informed Machine Learning (parameter inference, EnKF)
- Uncertainty quantification
- Climate networks
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.
My CV can be found here.
Publications and conferences
- Felix M. Strnad, Jakob Schlör, Christian Fröhlich, and Bedartha Goswami, Teleconnection patterns of different El Nino types revealed by climate network curvature, arXiv Preprint (2022), 2203.07035
- Schlör, J. and Goswami, B.: A data-driven generative model for sea surface temperature fields in the tropical Pacific, EGU21-12362, EGU General Assembly 2021