Prof. Dr. Melanie Schienle, Prof. Dr. Tilmann Gneiting
In all areas of science and society, big, complex and high-dimensional data is now ubiquitous. Machine learning and AI methods are already very effective at using such data for predictions.
The SIMCARD project will develop novel machine learning methods that are robust and reliable and go beyond simple predictions. The focus is on new methods for modelling very large networks and the reliability of predictions. The goal is to provide answers to pressing problems in a wide range of application areas with precisely fitting, scalable, sound and interpretable data science methods. The project addresses in particular the fields of data-intensive biomedicine and weather forecasting.