Our Network

Building on ambitious computational and data-driven research programs of the different faculties, the Interdisciplinary Center for Scientific Computing (IWR) serves as the hub for numerical and AI-driven research. Its groups are developing scientific AI methods for modeling, simulation, optimization, and data analysis. The corresponding AI applications cover the entire research spectrum of the university. For instance, biological data science uses scientific AI to translate large-scale omics data into biological insight, numerical chemistry uses generative AI to simulate reaction processes and their dynamics, while physics applies AI-methods to extract fundamental knowledge in data-intensive fields, such as environmental physics, astrophysics, and particle physics. 

These world-leading topical research programs combined with an established interdisciplinary culture and an excited and talented student population position Heidelberg University as a key hub for scientific AI research, from method development to high-profile applications.

Medical Systems Technology plays an important role in the research and clinical application of new diagnostic procedures and minimally invasive therapies. Examples include projects in the fields of radiomics and radiotherapy, but also in digital pathology and bioinformatics. The aim of research in Medical Imaging Informatics and Radiomics is the validation and standardization of quantitative imaging biomarkers including radiomics and their safe translation into clinical practice, and to evaluate the realistic potential of machine-based learning methods, including deep learning, for workflow optimization and diagnosis in radiology. The Mannheim Institute for Intelligent Systems in Medicine focuses on the holistic investigation of basic methods and applications of intelligent systems for preclinical care, diagnosis, therapy, and organization in the entire process chain, starting from the metrological acquisition of data, their analysis and modeling, up to their application on the patient.

Within the division for minimally invasive and robot-assisted surgery, the research group Artificial Intelligence and Cognitive Robotics investigates methods of AI and cognitive robotics to improve surgical treatment with a strong focus on clinical translation to help surgeons choose the best treatment option for the individual patient. Projects include predicting life-threatening complications during and after surgery via machine learning on multimodal process data, enabling personalized treatment decisions for patients based on data-driven approaches, providing data scientists with open surgical datasets to benchmark their algorithms, and annotating surgical data for the use in supervised machine learning as a basis for context-aware surgical assistance, robot-assisted surgery, and endoscopic vision challenges.

The CIMH has more than 1,400 employees and works closely with the University of Heidelberg and the Mannheim Medical Faculty of the University of Heidelberg.

The aim of the Hector Institute for Artificial Intelligence in Psychiatry (HITKIP) at the CIMH is to develop and apply advanced computational methods from the area of AI to uncover the causes of mental illness and thus contribute to the prevention and the improved clinical management of these disorders. The HITKIP combines the development of innovative AI technology, such as biologically informed and geo-distributed machine learning, interpretable machine learning models of dynamic neural systems, and advanced approaches for multimodal data integration into a coherent AI strategy geared towards the identification of illness and treatment-relevant effects. This research strategy is decidedly translational with the aim of implementing algorithms into tools that have a substantial positive impact on clinical care.