I am a complex systems physicists with a special interest on:
- Nonlinear time series analysis tools like climate networks and probilistic machine learning methods
- Global teleconnection structures of modes of variability (e.g. El Nino-Southern Oscillation)
- Spatial Organization of Extreme Rainfalls
A more detailed project description can be found here.
I obtained my Bachelor in Physics at the Georg-August University of Göttingen, followed by a specialization in Master of Physics of Complex Systems at the University of Göttingen. During my universtiy studies I spent one year at the University of Pisa. My Master’s thesis I wrote at the Potsdam Institute for Climate Impact Research (PIK). I spent one further year as a research assistant at PIK in the Real Estimate Climate Asset Mapping Project (RECAM). Since September 2020, I’m a PhD student in the Machine Learning in Climate Science group at the University of Tübingen and I’m part of the International Max-Planck Research School for Intelligent Systems (IMPRS-IS). Beside science, in my free-time I play in an orchestra, love to go running and doing sports.
My CV can be found here.
Felix M. Strnad, Jakob Schlör, Christian Fröhlich, and Bedartha Goswami, Teleconnection patterns of different El Nino types revealed by climate network curvature, Geophysical Research Letters, (2022), doi.org/10.1029/2022GL098571
Philipp Hess, Markus Drüke, Stefan Petri, Felix M. Strnad, Niklas Boers; Physically Constrained Generative Adversarial Networks for Improving Precipitation Fields from Earth System Models; Nature Machine Intelligence, (2022), doi.org/10.1038/s42256-022-00540-1
- Felix M. Strnad, Wolfram Barfuss, Jonathan F. Donges and Jobst Heitzig, Deep reinforcement learning in World-Earth system models to discover sustainable management strategies, Chaos (2019) doi.org/10.1063/1.5124673