Xiaolei is a PhD student in UBC Psychology’s clinical program. He graduated from UBC with an MA in psychology in 2017. His research centers on the prediction of problematic gamblers using machine learning algorithms with applications of big data. Xiaolei is interested in using behaviour variables to predict gamblers who are at risks of developing gambling addiction. The machine learning model can serve as a useful benchmark for other measures of problematic gambling and help refine the definition of problematic gamblers.

Xiaolei also hopes that this line of research can provide policy makers with applicable information, leading to better community protection and harm reduction.