The Chair for Computer Engineering researchs mainly design and verification of embedded hardware/software systems and mobile communication technologies as well as machine learning combined with neuronal networks, parallel computing and parallel and reconfigurable computer architectures, altogether supported by corresponding formal methods.
The research focus of the research group "Neural Interfaces and Brain Signal Decoding" is the application of methods of signal processing and machine learning to decode brain signals. First and foremost, the decoding of brain signals is to be used for the development and improvement of Brain-Computer Interfaces (BCIs). These interfaces between brain and computer enable a person to control a computer or external device (e.g. robot arm) by pure brain activity and should give completely paralyzed patients the possibility to communicate and interact with their environment. Furthermore, we are concerned with the evaluation of different brain signals with regard to neurobiological questions, as well as the application of machine learning methods in the general biomedical field.