We investigate high-capacity methods of machine learning and semantic technologies for scalable big data architectures. Our applied research is driven by our customers’ needs, by evolving trends in society, and by upcoming challenges in industry. We are providing analytics services for finance, healthcare, social media, mobility, and industry 4.0 applications. A special focus is on privacy-by-design and privacy-preserving data mining.
The knowledge discovery department of Fraunhofer IAIS will contribute its expertise and long-term experience in big data analytics to the REACH project. Our experts will guide the use of privacy-preserving data mining techniques to ensure the responsible handling of personal data that will be collected from patients in the scope of the project. Besides this, our department will engage in the analysis of the high-dimensional, multi-modal data streams generated by the sensory equipment, as well as in the integration and analysis of structured and unstructured data sources of medical patient data. The focus will be on multivariate time series analysis and automated rule learning systems, as well as process mining tools.