• Multi-modal data analysis

    We investigate techniques for joint analysis of data acquired from multiple modalities. One application is the analysis of the complex interactions within the autonomic nervous system.

  • Structure-revealing data fusion

    Identifying connected components in large datasets is challenging when measurements are scarce. This is particularly relevant in neuroscience for fusing data obtained from different modalities.


The Signal and System Theory Group welcomes you

We are a research group within the Paderborn Institute for Data Science and Scientific Computing (DaSco) and the Department of Electrical Engineering and IT at Paderborn University, Germany.

We work with data and signals, developing and researching techniques in artificial intelligence, machine learning, and statistical signal processing to generate, transform, extract, and interpret information.

Our focus is on the theory and the methods, but we are motivated by applications ranging from mobile communications to neuroscience and medicine.

We fuse data-driven and model-based approaches

We investigate and develop techniques that enhance the power of modern data-driven AI approaches, including deep learning, by incorporating a priori information in the form of models and expert domain knowledge.

Read more