About

Peng Huang is an Assistant Professor of Sociology at the University of Georgia. He received his PhD in Sociology and an MS in Statistics from the University of California, Irvine, trained in the Networks, Computation, and Social Dynamcis Lab. He also holds BAs in Sociology and Economics from Peking University.

Huang’s research focuses on social networks and population dynamics, adopting a relational and structural approach to explore social processes and people’s experiences therein. His first line of research examines how network dynamics and geopolitical contexts shape migration patterns. He studies the social and political cleavages contributing to the population immobility in the United States. Another paper critically engages with the phenomenon known as the “California Exodus.” Huang’s another research program investigates the spatial distribution of social relations. This line of inquiry offers insights into the diffusion of infectious diseases, including COVID-19, and the related health disparity issues.

Huang’s methodological work concentrates on developing statistical and computational methods to model network and population structures, dynamically and at a large scale. He studies computational methods that model valued/weighted networks, especially for large networks with high edge variance, under the framework of exponential-family random graph models (ERGMs). Alongside collaborators, he also develops imputation methods and algorithms for cross-tabulation data, which can be applied to infer distributions of multiple demographic characteristics in small areal units.

Huang is a recipient of the Geoffrey Tootell Dissertation Award from the Mathematical Sociology Section of the American Sociological Association, and the Best Student Paper Award from the International Network for Social Network Analysis (INSNA). His research articles have appeared in American Sociological Review, Journal of Mathematical Sociology, Proceedings of the National Academy of Sciences (PNAS), Social Networks, and Sociological Methodology.

Contact

Email: peng.huang [at] uga.edu
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