We conduct basic and applied research in computational and data-driven health technology with the purpose of improving human health and well-being while also enhancing delivery of healthcare. This is motivated by the constant demand for sustainable, participatory, preventive, personalized, economically tractable and better healthcare for all.
Our research topics include in particular biomedical signal/data/image processing and statistical learning for clinical decision support systems. Examples of our research are: i) predictive analytics for early disease onset detection and progression, ii) disease, disability and treatment monitoring at hospital or at home, and iii) information extraction from, often degraded, biomedical signals, data and images. In our work, we often address the following information pipeline:
We are open to collaboration with new partners from academia and industry on themes related to our research and development areas. Do not hesitate to contact us if you want to discuss collaboration opportunities. Students that are interested in doing projects with our group are also very welcome to contact us.
Our research activities are mostly externally funded via (inter)national grants and we have led and participated in numerous research projects and co-organized a number of conferences and workshops. Through our activities, we have had the privilege of working in close collaboration with leading partners from industry, academia and the public sector.
Our research group is organized under:
Section of Signal Processing and Machine Learning,
Department of Electrical and Computer Engineering,
Head of Group, Christian Fischer Pedersen
Associate Professor, MSc.CE, MSc.CS/Math, PhD
Union Rep., The Danish Society of Engineers (IDA)
Building: Edison (5125) (map)
Address: Finlandsgade 22, DK-8200 Aarhus N.