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Statistics, Data ScienceOffice: SCI 393
Mixture models; supervised and unsupervised learning; computational statistics and biostatistics.
Courses & Teaching
Statistics, data science.
I am currently holding a Postdoctoral Fellowship with Natural Sciences and Engineering Research Council of Canada (NSERC) under the supervison of Professor Jason Loeppky . In collaboration with researchers in the Irving K. Barber School of Arts and Sciences I have recently been exploring some statistical methods for detecting response to radiation on Raman spectroscopy data.
Prior to this, I was a post doctoral fellow working with Professor David Stephens at McGill University at the Department of Mathematics and Statistics . My post-doctoral work focused on the statistical and computational challenges associated with the analysis of genetic data.
I completed my PhD at the University of Guelph and was supervised by Professor Paul McNicholas . The topic of my PhD thesis was model-based classification and clustering with a particular emphasis on non-elliptical distributions. This research included the development of a “Fractionally-Supervised Classification” approach which unites the species of unsupervised, semi-supervised, and supervised classification under a single weighted-likelihood framework. under the supervision of Professor Rob Deardon and co-supervision of Professor Zeny Feng . My masters thesis involved modelling the spatio-temporal combustion dynamics of fire in a Bayesian framework.
PhD University of Guelph