In the course of the constantly increasing interconnection of the economy, accompanied by multiple and complex interdependencies between companies or even entire economic areas, quantitative risk management is becoming increasingly important. The Chair of Data Analytics & Statistics focuses its research and teaching on the resulting challenges.

At the interface between statistics and mathematical optimization, the research focus of the chair is on the development of innovative algorithms for prescriptive and predictive analytics. Based on the findings of the complexity theory of theoretical computer science, the trade-off between efficiency and optimality of the calculations must always be considered, since the algorithms have to prove themselves not only in theory but also in various practical application areas.

For teaching, this perspective implies in particular the imparting of a profound understanding of quantitative models. The focus here is deliberately not on the breadth but on the depth of the knowledge transfer, since the approach taught here enables the students to independently tackle further problem areas with the corresponding critical questioning.

Further information

Further information about research, teaching and the team of the chair can be found here.