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. The research in the group revolves around two pillars: mathematical statistics and industrial statistics. 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).
Members
Affiliated Members
Recent Publications*
* – Disclaimer: this list is automatically recovered from the TU/e Pure repository. Due to difficulties in integrating the pure API in wordpress there might be repetitions and it might not be fully representative of all recent publications.