Yiang Li is a PhD student in Sociology at the University of Chicago. He is also a Predoctoral Trainee in the NIA T32 Program in the Demography and Economics of Aging at the Center on Healthy Aging Behaviors and Longitudinal Investigations (CHABLIS) and a graduate student affiliate at the Stone Center for Research on Wealth Inequality and Mobility at the University of Chicago.

As a sociologist and social demographer, Yiang studies social stratification, and particularly health disparities, examining how micro-level contexts of family and meso-level contexts of neighborhood and concentrated poverty jointly shape health and aging. His research uncovers the early-life precursors and underlying mechanisms through which these contexts 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 combines statistical and demographic methods with computational tools, with a particular focus on causal inference, machine learning, record linkage, and high-performance computing. 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.

Yiang received his MA in Computational Social Science from the University of Chicago in 2024 and BSc (First Class Hons) in Social Sciences with Quantitative Methods from University College London (UCL) in 2022.

His research work has been published in Social Forces, Social Science Research, Social Science & Medicine, and Demographic Research, among other peer-reviewed journals.

Yiang can be reached via email: yiangli@uchicago.edu and his CV can be found here.