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Intelligent systems are characterized by learning processes that allow the acquisition of new skills and deal with a large amount of heterogeneous, uncertain and probabilistic data. Due to the complexity of the real-world situations represented by them, the automatic abstraction of information from data, the formation of appropriate representative models, and the semantic processing of existing information is essential to build intelligent systems for digital transformation, such as mobility To enable industry, medicine and education.


Umfassende datengestützte Risiko- und Bedrohungsbewertungsmethoden zur frühzeitigen und zuverlässigen Identifizierung, Validierung und Analyse von migrationsbezogenen Risiken

CRiTERIA is a novel, comprehensive, and human-rights sensitive risk and vulnerability analysis framework based on multi-perspective, multi-source, multi-lingual technologies.






Prediction of electric vehicle charging demand as business enabler






Data4UrbanMobility focuses on facilitating innovative mobility services and mobility-related infrastructure development in smart cities through comprehensive data analytics







Digitization of plant and animal species occurrence records for documenting the extent of biodiversity loss.

Discovering Job Knowledge from Web Data

Discovering Job Knowledge from Web Data




Establishing and achieving sustainable targets in Eastern Chinese cities




eLabour II

Interdisciplinary Centre for IT-based Qualitative Research in Work Sociology




Project extention for a orthograhic training methode





ZL Produktion

Digital modelling and optimization




Haisem Lab

Labor for methodical development of high-performance AI-applications for modern hardware-Architectures