Suyeon Kang

Suyeon Kang is an Assistant Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF), within the College of Sciences. Her research focuses on multivariate analysis, causal inference, sensitivity analysis, and mixture models, with applications in disparities research, social sciences, and health sciences. She previously served as a postdoctoral researcher at the University of Florida.

Education:

• Ph.D. in Applied Statistics, University of California, Riverside (2022)
• M.S. in Statistics, Ewha Womans University (2017)
• B.S. in Statistics and B.E. in Economics, Ewha Womans University (2014)

Research Interests: Her work bridges statistical methodology with interdisciplinary applications, emphasizing causal decomposition analysis, partial identification of causal effects, and methodological advancements in handling unmeasured confounding. She develops statistical software tools (e.g., R packages like MixSemiRob and rrMixture) to support robust data analysis in complex systems.

Publications: Kang’s recent work includes studies on causal decomposition in STEM disparities, sensitivity analysis frameworks, and computational methods for mixture models. Her research often addresses societal challenges through rigorous statistical approaches.

Awards/Grants: No awards explicitly listed, but her postdoctoral and faculty roles reflect sustained scholarly engagement. Grants and funding details are not provided in the text.