Wolfgang Polonik

Wolfgang Polonik is a Professor in the Department of Statistics at the University of California, Davis, where he conducts research at the intersection of mathematical statistics, nonparametric methods, and topological data analysis. His work combines deep theoretical foundations with applications in high-dimensional and complex data structures.

His research interests include Mathematical Statistics, Statistical Learning Theory, Nonparametric Statistics, Shape Constraints, Modality, Nonstationary Time Series, Empirical Process Theory, Topological Data Analysis, and Random Networks. He applies these to problems involving geometric and topological inference, manifold learning, and anomaly detection.

The recent publications highlight a strong focus on persistent homology, bootstrap methods for topological features, nonparametric regression on manifolds, and multiscale geometric analysis. His work often bridges theoretical statistics with computational topology and machine learning, particularly through the use of persistence diagrams, level sets, and filament estimation. Collaborations with researchers like W. Qiao and G. Chandler are frequent.

Dr. Polonik has served as an Associate Editor for several top-tier journals, including:

• Journal of the Royal Statistical Society – Series B (2012–2015)
• Journal of Multivariate Analysis (since 2003)
• Journal of Statistical Planning and Inference (2004–2012)
• Annals of Statistics (2007–2012)

He is a member of leading professional societies such as the Institute of Mathematical Statistics, American Statistical Association, Bernoulli Society, and International Statistical Institute. While no formal advising or grant information is listed, his editorial roles and publication record reflect significant scholarly impact. He is affiliated with the College of Letters and Science at UC Davis.