Research Themes

My research develops and applies statistical and machine learning methods for complex health data, with a particular focus on understanding human behaviour and its relationship with health across the life course. My research is broadly organized around three complementary themes:

Theme 1: Statistical Learning for Complex Health Data
Developing and applying Bayesian and machine learning methods for complex longitudinal, functional, and high dimensional health and kinesiology data.

Theme 2: Digital Phenotyping and Multimodal Data Integration
Developing and applying statistical and machine learning methods to integrate wearable sensors, geospatial information, and other multimodal data to characterize human behaviour, exposome, and health across the life course.

Theme 3: Biostatistical Collaboration and Translational Research
Providing biostatistical leadership across interdisciplinary research projects and translating findings into meaningful insights for health research.