Prof. Dr. Daniel Rückert – Gottfried Wilhelm Leibniz Prizewinner 2025
Artificial Intelligence, TU Munich
Artificial intelligence and machine learning methods are already widely used in medicine, including in imaging techniques – an area in which Daniel Rückert has done pioneering work. He has developed novel algorithms that can be used to reconstruct, analyse and interpret biomedical images, work which has significantly accelerated the image-taking process and given rise to novel methods for reconstructing CT and MRT image data. As a result, diseases can now be diagnosed and treated more effectively and more individually. Rückert presented his first studies on non-rigid and multimodal registration as early as the 1990s. This made it possible to link medical image data across different time points and modalities. He has also proposed powerful algorithms in the field of machine learning. In more recent studies, Rückert has also established 3D reconstruction using machine learning, which is used primarily for MRI data.
Daniel Rückert studied computer science at the Technical University of Berlin and obtained his doctorate at Imperial College London, after which he took up a postdoc position at King’s College London, UK. In 1999, he became an assistant professor at Imperial College, and six years later, he was appointed to a professorship in visual information processing at the Department of Computing, which he chaired from 2016 to 2020. Since 2020, he has been Alexander von Humboldt Professor of Artificial Intelligence in Medicine and Healthcare’ at the Klinikum rechts der Isar of TU Munich. Rückert’s memberships include the German National Academy of Sciences Leopoldina, the Berlin-Brandenburg Academy of Sciences and Humanities (BBAW), the Royal Academy of Engineering, the Academy of Medical Sciences and the Institute of Electrical and Electronics Engineers (IEEE).
GEPRIS
In our information system GEPRI you will find an overview of current and completed projects of Professor Dr. Daniel Rückert.