Multivariate extremes

Exploring Non-Linear Interactions in Multivariate Time Series

-

KAUST

Advances in imaging technology have given neuroscientists unprecedented access to examine various facets of how the brain “works”. Brain activity is complex. A full understanding of brain activity requires careful study of its multi-scale spatial-temporal organization (from neurons to regions of interest; and from transient events to long-term temporal dynamics). Motivated by these challenges, we will explore some characterizations of dependence between components of a multivariate time series and then apply these to the study of brain functional connectivity.

Congratulations to Zhongwei for successfully defending his PhD thesis

1 min read ·
Left: Zhongwei before starting his PhD defense. Right: picture taken at the group dinner following the defense, with Zhongwei (center) and Prof. Raphael Huser (carrying a child next to Zhongwei)

Congratulations to Yan for successfully defending her PhD thesis

1 min read ·

Pavel Krupskiy

Postdoctoral Research Fellow, Statistics
Krupskiy, Pavel Postdoctoral Fellows ​​Ph.D. 2014, University of British Columbia, Canada​​ Now Assistant Professor at University of Melbourne Education ​ Ph.D. in Statistics 2014, University of British Columbia, Canada M.A. in Economics 2009, New Economic School, Russia B.Sc. in Mathematics 2006, Lomonosov Moscow State University, Russia Research interests copulas, multivariate extremes, nonparametric statistics, spatial data