Statistics

The statistics group focusses on developing sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the aim to perform predictive, prescriptive or preemptive analytics. Our research activities are heavily intertwined with applications, e.g., process monitoring and improvement, weather forecasting and causal inference. Topics are ranging from heavily data-driven to fundamental and methodological aspects, including causality, dependence structure models, high-dimensional and non-parametric statistics and sequential decision making and data collection. The group collaborates closely with the Teaching & Research Institute for Data Science Analytics (TRI-DSA).