Yongseok Lee is a post-doctoral associate at the Bureau of Economic and Business Research (BEBR) & Clinical and Translational Science Institute (CTSI) Network Science Lab at the University of Florida.

Yongseok’s primary research agenda is a causal inference in complex and incomplete structured datasets. On the methodological issue for estimating precise causal inference, he suggested a matching algorithm in the cross-classified data structure, a missing imputation method with a machine learning approach, and the effect of mismeasured variables. His recent work focuses on combining network structure and unstructured information (e.g., Natural Language Processing) into the causal inference framework and investigating the causality in the measurement of the issue of inequity that can occur in testing and survey.