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Sujin Wang is a Professor in the Department of Statistics at Texas A&M University, where he specializes in biostatistical inferences and methodologies for analyzing complex data. His research interests include the development of models for missing and mis-measured data, non-parametric and semi-parametric statistical methods, as well as resampling techniques and small sample asymptotics. He also explores issues related to survey sampling, contributing to the advancement of statistical theory and practice. With a strong focus on improving data analysis methods, Wang actively engages in research that enhances the understanding of statistical challenges in various fields. His work is pivotal for applications requiring precise data modeling and inferencing.
Department: Department of Communication and Journalism. Ph.D. program only currently admitting. GRE is test-optional.