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.
