Our research and teaching activities aim at data mining and machine learning principles for applications in engineering, the life sciences, and web/online services. The huge amount of data, the complexity of the data instances, and the presence of potential corruptions and noise are limiting factors for analyzing and understanding real world datasets. We face these challenges by developing robust and efficient concepts for data analysis.