Research

Klaus-Robert Müller studied neural networks and their theoretical properties using methods from statistical mechanics, asymptotic statistics and computer science until the beginning of the 90s. Since the mid 90s he contributed significantly to the mathematical and computer science foundations of machine learning and established the research field of kernel-based learning and Support Vector Machines and engaging in its wide application in the sciences and industry.

His research focus is the development of novel kernel-based learning methods for quantum chemistry and for the neuro sciences, in particular for non-invasive Brain-Computer-Interfacing. Further topics of interest are the better understanding of nonstationary data and multi-modal data analysis.