Dr. Zhu holds a Master’s Degree in Statistics from the National University of Singapore and a PhD from Pennsylvania State University. Currently, she is Associate Professor in the Department of Statistics & Actuarial Science at the University of Waterloo.

Dr. Zhu’s research interests lie in causal inference, machine learning, and the interface between the two. She is keen to understand the interdisciplinary nature of causal inference and aims to develop theoretically sound methods for data-driven problems. Her recent work focuses on the development of variable-selection and dimension-reduction procedures to adjust for confounding in observational studies. She is also exploring causal mediation analysis, which examines how a treatment or intervention affects the outcome through one or more intermediate variables. Notably, Dr. Zhu has developed innovative machine learning algorithms for the modeling of propensity scores for binary, multi-level, and continuous treatments. Applications of Dr. Zhu’s research lie in biomedical studies, public health, and social sciences.