Congratulations Peijun Sang, 2019 Pierre Robillard award recipient!

Wednesday, May 8, 2019

The Statistical Society of Canada (SSC) awarded Peijun Sang as the winner of the 2019 Pierre Robillard Award of the Statistical Society of Canada. This prize recognizes the best PhD thesis in probability or statistics defended at a Canadian university in a given year. Peijun’s thesis, entitled “New Methods and Models in Functional Data Analysis" was written while he was a doctoral student at the Simon Fraser University, working under the supervision of Jiguo Cao.

His current research interests are focused on functional data analysis methods. Data from electroencephalogram signals, function magnetic resonance imaging and diffusion tensor imaging are important examples. He is interested in applying functional data analysis techniques to study functional connectivity between imaging data collected from different regions of the brain. He is concerned with large sample properties of high dimensional functional regression models that have been proposed for this type of data. He is also interested in dependence modelling with copulas for discrete and time-to-event outcomes.

Peijun SangImage: Professor Peijun Sang

This work is an excerpt from the SSC website, written by Gordon Fick.