Dr. Michael Langguth
Michael Langguth is a Postdoctoral Scientist at the Jülich Supercomputing Centre at Forschungszentrum Jülich, leading the ‘Deep Learning for Weather and Air Quality’ team within the ‘Earth System Data Exploration’ group. He earned his PhD and Master of Science in Meteorology from the University of Bonn. His research focuses on developing robust deep learning methods for meteorological applications, including statistical downscaling and super-resolution of air quality data. He is also involved in the AtmoRep project, applying AI technologies to atmospheric dynamics. Previously, he worked as a scientific researcher at Forschungszentrum Jülich and as a PhD student at the University of Bonn.
Prof. Dr. Martin Schultz
Martin Schultz is the Group Leader of Earth System Data Exploration at the Institut Jülich Supercomputing Centre at Forschungszentrum Jülich and Division Co-lead for Large Scale Data Science. He holds a PhD in Physical Chemistry and a Habilitation in Meteorology, with a professorship in Computational Earth System Science at the University of Cologne since 2024. His research focuses on large-scale deep learning and FAIR data management for air quality, weather, and climate modeling. Previously, he held leadership roles at the Max-Planck-Institute for Meteorology and Forschungszentrum Jülich.
Prof. Dr. Christian Lessig
Christian Lessig is a machine learning expert at ECMWF, the Eropean Center for Medium Weather Forecast. His background is in computer science but he also works today in scientific computing and numerical analysis. In the last years, his research moved towards addressing climate change, in particular by developing hybrid weather and climate simulation models that combine classical discretizations of the governing partial differential equations with neural networks that account for phenomena that are too expensive to simulate or whose physics is not well understood
Dr. Ilaria Luise
Ilaria Luise is working as Machine Learning scientist at ECMWF. She is involved in the RAINA and WeatherGenerator projects. Her background is in experimental physics and uncertainty quantification of complex physics processes. She owns a PhD in High Energy Physics at Sorbonne University and she worked for almost 10 years at CERN before moving to ECMWF. She was co-PI of the AtmoRep project and her current research interests focus on the evaluation and diagnostics of Machine learning models for weather and climate.
Prof. Dr. Jürgen Gall
Juergen Gall is professor and head of the Computer Vision Group at the University of Bonn since 2013, spokesperson of the Transdisciplinary Research Area “Mathematics, Modelling and Simulation of Complex Systems”, and member of the Lamarr Institute for Machine Learning and Artificial Intelligence. After his Ph.D. in computer science from the Saarland University and the Max Planck Institute for Informatics, he was a postdoctoral researcher at the Computer Vision Laboratory, ETH Zurich, from 2009 until 2012 and senior research scientist at the Max Planck Institute for Intelligent Systems in Tübingen from 2012 until 2013. He received a grant for an independent Emmy Noether research group from the German Research Foundation (DFG) in 2013, the German Pattern Recognition Award of the German Association for Pattern Recognition (DAGM) in 2014, an ERC Starting Grant in 2016, and an ERC Consolidator Grant in 2022.
Anas Al-lahham
Anas Al-lahham is a PhD student at the University of Bonn, working in the Computer Vision Group (CVG) under the supervision of Prof. Juergen Gall. His research focuses on foundational models for weather forecasting, video anomaly detection (VAD. Previously, he earned his Master’s degree in Computer Vision at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE. He also holds a bachelor’s degree in Electrical Engineering from King Saud University (KSU). His main research interest is Weather Forecasting and multi-model early action prediction, with an emphasis on leveraging advanced computer vision techniques and foundational models to address challenges in these domains.
Dr. Stefanie Hollborn
Stefanie Hollborn is a scientist at the German Weather Service (Deutscher Wetterdienst, DWD) and leads the Department of Observation Modeling and Verification. She holds a PhD in Numerical Mathematics with a specialization in Inverse Problems from the University of Mainz. Her research focuses on developing and implementing data assimilation methods to enhance Numerical Weather Prediction. Recently, her work has increasingly concentrated on the application of artificial intelligence in weather forecasting and weather and climate services.
Dr. Sabrina Wahl
Sabrina Wahl is a postdoctoral researcher with a background in statistical methods for the atmospheric sciences. From 2013 to 2022, she worked on verification methods and statistical post-processing for weather and climate simulations within the Hans-Ertel-Centre group on Climate Monitoring and Diagnostics. In 2023, she joined the FE12 verification group at DWD with a focus on data-driven weather forecasts.