​I obtained my Ph.D. degree in Statistics - Biostatistics from the University of Waterloo in 2013. My doctoral dissertation studies diverse problems in event history analysis, but all with a general theme involving complex dependencies modelled by copula functions, which brought me the 2013 Pierre Robillard Award of the Statistical Society of Canada for the best doctoral thesis in probability or statistics defended at a Canadian university in 2013. I worked as a postdoctoral associate in the Department of Biostatistics and Computational Biology at the University of Rochester in the United States in 2014. My postdoctoral experiences at Rochester got me to start research on the development of novel statistical methods for building, selecting and evaluating relevant risk indices using recursive partitioning and other machine learning methods for survival data. I started to work as an assistant professor in the Department of Statistics and Actuarial Science at the University of Waterloo since 2015. I expanded my research to a broad spectrum of areas including recursive partitioning learning, causal inference, dependence modeling, Bayesian methods, and two-phase design.