Irene Vrbik

Assistant Professor of Teaching

Data Science, Mathematics, Statistics
Office: SCI 104
Phone: 250.807.8872

Graduate student supervisor

Research Summary

Mixture models; supervised and unsupervised learning; computational statistics and biostatistics.

Courses & Teaching

Statistics, data science.


I am currently an Assistant Professor of Teaching in the subject area of Statistics and Data Science.  As an Educational Leadership faculty, I am interested in applying Machine Learning techniques to help understand and improve curriculum.

Previous to this position, I held a Postdoctoral Fellowship with Natural Sciences and Engineering Research Council of Canada (NSERC) under the supervision of Professor Jason Loeppky . In collaboration with researchers in the Irving K. Barber Faculty of Science, we have explored 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


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