Bio

Jan Greve is a PhD student at WU Vienna University of Economics and Business, Institute for Statistics and Mathematics. He holds a BA in economics (Waseda University) and an MSc in statistics (Duke University). His current research interests center around the subject of Bayesian model-based clustering. In particular, he is interested in developing tools for applied researchers in this field to better understand the characteristics of the prior distribution on the set of all possible partitions. Methodologically, this amounts to finding ways to carry out combinatorial enumeration of weighted partitions. He believes that symbolic computation is the most well-suited way to tackle this type of problem. On a more general note, he is interested in statistical models (mostly Bayesian) that treat nontrivial objects, such as partitions, graphs, etc., as random. Such an area is a rich intersection between combinatorics and statistics worth exploring. In his spare time, he enjoys outdoor activities such as mountaineering and skiing. Traveling is also his passion and he particularly likes to collect replicas of the historical maps of the cities he visits.

Project: Riordan Arrays for the enumeration of combinatorial structures