We are dedicated to learning and inference of large statistical models from data. Our focus includes optimization of machine learning models, validation of algorithms and large scale data analytics. Data driven scientific modeling permeates all areas of natural science, engineering, social science and more recently also humanities. The resulting methodological challenges strongly suggest to combine high performance algorithmics and cutting edge statistical modeling. Applications range from medicine and the life sciences to distributed sensing and natural language processing.