Professor Dr Klaus-Robert Müller

Research Priorities: Artificial intelligence, brain-computer interfaces, machine learning, neural networks, computational neuroscience, big data
Klaus-Robert Müller is a German physicist and computer scientist. He is considered a pioneer of modern machine learning. His work on support vector machines has provided a key basis for contemporary deep learning processes. He researches brain-computer interfaces and strives to create transparency concerning the workings of complex AI models.
In brain-computer interfaces (BCI), electroencephalography (EEG) is used to record brain activity. Learning algorithms can then translate these into signals to control external devices. Klaus-Robert Müller’s team have reduced the calibration time of non-invasive BCI systems from hours to less than 20 minutes and have subsequently developed the zero-training paradigm, by means of which the system can teach itself during use. A study with severely paralysed patients showed that they can use this technology to interact and communicate with their environment faster than with muscle-based systems.
In other studies, Klaus-Robert Müller has examined how the brain processes compressed video content and how it reacts to modern LED light sources. He discovered that the brain actively processes the flickering of light sources. In his research he looks for solutions to help the brain “relax” under such conditions. With respect to big data, he wants to professionalise data analytics in order to maximise the insights that can be gained from collections of data. 
Since 2015, Müller has placed greater focus on “Explainable AI” (XAI) in order to make black box models transparent and trustworthy. The standard work “Explainable AI: Interpreting, Explaining and Visualizing Deep Learning”, which he coedited in 2019, has significantly structured this subject area. At the same time, Müller also applies machine-learning methods to quantum chemistry and materials research.
This work allows him to create trustworthy AI solutions that help severely paralysed people communicate, and also help improve visual well-being, transparently evaluate clinical omics data, and accelerate the discovery of sustainable materials as well as catalysts. His research is interdisciplinary in nature and aims to create specific applications in the neurosciences, medicine, and quantum chemistry that benefit society.