Avery Wang is a PhD student with a strong interest in the intersection of aging biology, statistical modeling, and artificial intelligence. Her research focuses on uncovering patterns of biological aging by identifying novel biomarkers that enhance our understanding of age-related health trajectories. Leveraging large-scale datasets like the UK Biobank, Avery applies advanced statistical techniques and AI-driven tools to analyze biological signals, particularly hormones and omics data, in relation to disease onset and mortality. He is especially interested in developing interpretable models that quantify biological age and uncover mediating pathways linking early-life exposures to aging-related outcomes. Through this work, Avery aims to contribute to the development of precision health strategies for aging populations.