Zihang Lu (Queen’s)

Math & Stats Department Colloquium

Friday, December 1st, 2023

Time: 2:30 p.m.  Place: Jeffery Hall, Room 234

Speaker: Zihang Lu (Queen’s)

Title: Integrating Multidimensional Longitudinal Features to Discover Disease Phenotypes: A Bayesian Consensus Clustering Approach

Abstract: Clustering longitudinal features is a common research goal in health studies to identify distinct developmental patterns that reflect disease phenotypes and to facilitate targeted intervention. Compared to clustering a single longitudinal feature, integrating multiple longitudinal features allows additional information to be incorporated into the clustering process, which reveals co-existing developmental patterns and generates deeper biological insight. In this talk, I will discuss a newly developed Bayesian clustering approach for clustering multidimensional and high-dimensional longitudinal features with complex data structures. Results from analyzing birth cohort data to discover respiratory phenotypes will be presented and discussed.

Bio: Dr. Zihang Lu is an Assistant Professor in the Department of Public Health Sciences at Queen’s University, with a cross-appointment to the Department of Mathematics and Statistics. He completed an MSc and PhD in Biostatistics from the University of Toronto. Dr. Lu’s research focuses on statistical and machine learning methods motivated by high-dimensional and large health data with complex structures. His research is supported by funding from the Natural Sciences and Engineering Research Council of Canada and the Canadian Institutes of Health Research.