Sunghee Lee is a Research Professor in the Survey Methodology Program at the Survey Research Center, Institute for Social Research, where she directs the Program in Survey and Data Science. She earned her PhD from the Joint Program in Survey Methodology at the University of Maryland. Before joining the University of Michigan, she served as a Survey Methodologist for the California Health Interview Survey and as an Adjunct Assistant Professor of Biostatistics at UCLA.

As a methodologist, her research advances the study of data quality through a focus on inclusivity, with important implications for equity in social programs and policy decisions. Her work addresses two central dimensions of data quality: representation and measurement. She identifies and examines sources of error that can compromise inclusivity—including coverage, nonresponse, translation, question order, and response style—often at the intersection of survey methodology and cultural norms. She leads the sampling component of the Health and Retirement Study and serves as principal investigator on multiple studies that use respondent-driven sampling to recruit hard-to-reach population subgroups, including immigrant populations. Her work also explores the potential of emerging technologies to improve data inclusivity and strengthen data quality.