Marlene Kretschmer

Marlene studied mathematics before completing a PhD in climate physics at the Potsdam Institute for Climate Impact Research. She then worked as a postdoctoral researcher in the Department of Meteorology at the University of Reading (UK). Since 2022, she is a Junior Professor of Climate Causality at Leipzig University. Her research aims to understand the large-scale drivers of regional weather and climate, including extreme events, and how this knowledge can enhance predictions from subseasonal timescales to projections extending to the end of the century. She is particularly interested in applying causal inference and machine learning algorithms to identify key drivers and teleconnections in large climate model simulations and observational datasets. Her approach integrates data-driven methods with physical understanding to improve climate prediction and interpretation.

Sebastian Engelke

Sebastian is Associate Professor at the Research Institute for Statistics and Information Science at the University of Geneva, where he is holding an Eccellenza grant. His research group works on: Extreme value theory and graphical models; extrapolation in machine learning; AI weather forecasting; and statistical climate science. Sebastian did his studies in Mathematics at University of Göttingen and UC Berkeley, and he obtained his PhD in 2013 at the University of Göttingen. He was then an Ambizione fellow at EPF Lausanne with Anthony Davison, and visiting professor at the Department of Statistical Sciences at the University of Toronto from 2018–2019.