All students under my sole supervision unless explicitly stated otherwise.


Name Research Topic Year Completed  Current/Last Known Position
Robyn Bates, Co-supervised with Bill Reed An exploration of Bayesian methods for the generalized normal-Laplace distribution 2006
Psychology Undergraduate Student, UVic
Philip Rempel Exploring model misspecification and robustness in joint models for longitudinal and survival data. 2007
Not Known
Eric Cormier Exploring Markov models for longitudinal binary data 2009Assistant Teaching Professor, Mathematics and Statistics, UVic
Elena Szefer Statistical Approaches for Combining Group Analysis and Registration of MR Images 2012
Biostatistician, The EMMES Corporation
Robin Spilette, Co-supervised with Naznin Virji-Babul
Graph theoretic analysis of EEG data
Law Student, University of Toronto
Robyn Kilshaw, Co-supervised with Mike Masson
Bayesian Within-Subject Credible Intervals for Repeated Measures Designs
In Progress

Graduate MSc:

Name Research Topic Year Completed   Current/Last Known Position
Hong Li                                                   Spatio-temporal modeling of fire frequency and severity from panel data. 

Research award: Best poster award – 19th Annual Conference of The International Environmetrics Society, 2008.
2008Statistician, Health Canada
Aijun Yang                                              Modeling survival after myocardial infarction using accelerated failure time models and space-varying regression. 2009Statistician, Health Canada
Parminder Sarohia A study of desperation in sport. 2010Actuarial Position, Mercer, Vancouver
Salimah Ismail Mixed model and space-varying regression analysis of Magnetoencephalography  brain signals.

Research award: Best student research presentation – 40th Annual Meeting of the Statistical Society of Canada, 2012. 
Susan Kinniburgh Spatial and Network models for the spread of disease. 2012
Regular Faculty Member, Mathematics and Statistics, Camosun College, Victoria
Priya Grewal Spatial smoothing and ecological regression analysis of low birth weight in British Columbia. 2012
Veronica Sabelnykova, Co-supervised with Mary Lesperance
Bayesian Methods for Joint Modeling of Survival and Longitudinal Data: Applications and Computing
Statistician, Ontario Institute for Cancer Research, Toronto
Keelin Greenlaw, Co-supervised with Mary Lesperance 
Bayesian group-sparse multi-task regression for imaging genomics.

Research award: CANSSI-sponsored best paper award - Statistical Society of Canada Student Meeting, 2015.
Statistician, Lady Davis Institute for Medical Research, Montreal
Nicole Croteau
Persistent homology for MEG/EEG classification with application to brain decoding.
Statistical Consultant, UVic Statistical Consulting Centre
Laila Yasmin
Relating resting-state fMRI effective connectivity in the default mode network to genetics with dynamic causal models and  group-sparse multi-task regression.
In Progress

Graduate PhD:

Name Research Topic Year Completed  Current/Last Unknown Position
Angus Argyle  Species Richness Estimation
Statistician, Statistics Canada, Ottawa
Ming Teng, Co-supervised with Timothy Johnson
Bayesian Computation for Spatial Data and Neuroimaging Data
Statistician, AIG, New York
Yin Song
Statistical Methods for Neuroimaging Data Analysis and Cognitive Science
In Progress

Eugene Opoku, Co-supervised with Ejaz Ahmed
Methods for Neuroimaging Data and High-Dimensional Data
In Progress

Shan Shi
Deep Learning with applications to brain decoding and imaging genetics
In Progress

Postdoctoral Fellow:

Name Research Topic Year Completed  
Li Xing(NSERC and UVic PDF)                                                                    
Regression for Longitudinal Analysis in Imaging Genetics with Bayesian Shrinkage Priors
In Progress


Research Associate:

Name Research Topic Year Completed  
Susan Kinniburgh, Co-supervised with Trisalyn Nelson (Geography)                                                                      
High-dimensional analysis for predictive crime mapping 2014
Nicole Croteau, Co-supervised with Trisalyn Nelson (Geography)
Machine learning for forecasting expected hydrological runoff

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