Current Postdoctoral Fellows
-
Holly Steeves (co-supervise with Laura Cowen (UVictoria) and Simon Bonner (Western)
Current Graduate Students
-
Arjun Banik (Ph.D., Current, co-supervise with Laura Cowen at UVictoria)
-
Christophe Turcotte-van de Rydt (M.Sc., Current, co-supervise with Kevin Fraser)
-
Elham Afzali (Ph.D., Current, co-supervise with Liqun Wang)
-
Samuel Morrissette (M.Sc., Current, co-supervise with Jason Fiege)
-
Courtney Bonner (M.Sc., Current)
-
Surani Mathara Arachchige (M.Sc., Current, co-supervise with Mike Domaratzki)
-
Ashani Wickramasinghe (M.Sc., Current)
-
Adriana-Stefania Ciupeanu (Ph.D., Current, co-supervise with Julien Arino)
-
Qiao Tang (M.Sc., Current, co-supervise with Xikui Wang)
-
Inesh Munaweera (Ph.D., Current, co-supervise with Darren Gillis)
-
Lahiru Wickramasinghe (Ph.D., Current, co-supervise with Alex Leblanc)
-
Ankit Doshi (Ph.D., Current, co-supervise with Brad Johnson)
Former Graduate Students
-
Laurence Cuny (M.Sc., 2020 co-supervised with Katherine Davies)
Thesis: Order Restricted Bayesian Inference of the Simple Step-Stress Model under Type-I Right
Censoring with Weibull Distributed Lifetimes.
-
Isuru Dharmasena (M.Sc., 2020)
Thesis: Modeling and Simulation of Mobile Apps User Behavior.
-
Weijia Zhang (Ph.D., 2019, co-supervised with Po Yang)
Thesis: Novel statistical designs for phase I clinical trials.
-
Mohammed Mujaab Kamso (M.Sc., 2018, co-supervised with Saumen Mandal)
Thesis: Network Meta-Analysis Using Bayesian Methods and Some Diagnostics.
-
Inesh Munaweera (M.Sc., 2018, co-supervised with M. Jafari Jozani)
Thesis: Shrinkage Estimators under Generalized Garrote and Linex Loss Functions for Regression Analysis. -
Lahiru Wickramasinghe (M.Sc., 2015)
Thesis: Non-Inferiority Hypothesis Testing in Two-Arm Trials with Log-normal Data.
-
Peng Zhang (M.Sc., 2014)
Project: Social Network Analysis using Exponential Random Graph Models.
-
Cynthia Kpekpena (M.Sc., 2014)
Thesis: Bayesian Analysis of Binary and Count Data in Two-arm Trials.
-
Jing Zhang (M.Sc., 2012)
Project: Bayesian Methods for Modeling and Analyzing Item Response Data.