Michelle has extensive experience working with diverse methodologies using various types of databases, including administrative linked data, survey-based cohort data, and clinical trial data. Her previous research primarily focused on marginalized populations, such as people using drugs and individuals living with HIV. Her doctoral research focused on unregulated drug use and the effectiveness of its treatment. She applies machine learning techniques to uncover underlying drug use patterns and to understand their relationship with drug treatment engagement within a causal inference framework. Michelle holds a PhD in Public Health and an MSc in Statistics from the University of British Columbia.

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