Cluster of Excellence “Machine Learning”
Maria-von-Linden-Str. 6
72076 Tübingen

Research Interests

I am researching spatio-temporal neural networks for climate processes. The goal of my work is to enable deep learning forecasts of climate events on seasonal-to-subseasonal scales.

Topics of interest include the tropical pacific with its characteristic El Nino Southern Oscillation pattern, as well as the Madden-Julian Oscillation and its effect on extreme rainfall in southeast Asia.

Methodologically I am interested in self-supervised learning, generative models and conditioning methods for scalable Transformer architectures.


My background is in cognitive science, with a primary interest in learning and general (artificial) intelligence. During my studies I worked on decision-making and learning of categories, analysis of MR images and collective information processing.

Machine learning has been the focus of my studies and research throughout and climate science is now providing an amazingly complex, challenging and important source of data to explore. I am mainly interested in methodological underpinnings of spatio-temporal models.

In my free time I enjoy bouldering, reading and playing games.