About
Jan Greve is a Researcher at the Institute for Statistics and Mathematics at Wirtschaftsuniversität Wien (Vienna University of Economics and Business). His research focuses on Bayesian statistical methods, including cluster analysis, mixture models, and metadata anonymization. He has contributed to both theoretical advancements and practical software tools in computational statistics.
Greve's recent work includes developing novel approaches for partition structures in Bayesian nonparametrics and creating anonymization techniques for text corpora. He has authored/co-authored peer-reviewed articles and preprints, alongside software contributions like the 'fipp' package for Bayesian mixture models.
He has actively participated in academic activities such as presenting on topics like 'Mixtures of finite mixtures and the telescoping sampler' at international conferences. His research bridges theoretical statistics with applied data science challenges.
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