As a sociologist and social demographer, Yiang studies how social inequality,
particularly health disparities, is produced through social contexts, with a
focus on family structures and neighborhood poverty. His research focuses on
uncovering early-life precursors and underlying mechanisms through which
family and place shape, perpetuate, and reproduce health differentials and
social disadvantages from one generation to the next using temporal,
developmental, and place-based perspectives. Additionally, he adopts a
comparative perspective to study how contemporary and historical population
processes across countries are linked to morbidity and mortality patterns.
Yiang's research applies statistical, demographic, and computational
techniques, with a particular focus on causal inference, data linkages,
large-scale analytics, and machine learning. He completed a doctoral
certificate in
Advanced Quantitative Methods. In addition to his research, he has taught statistics, data science, and
computational methods, at both the undergraduate and graduate levels.
His research work has been published in Social Forces,
Social Science Research, Social Science & Medicine, and
Demographic Research, among other peer-reviewed journals.