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Sunmee Kim is an Assistant Professor in Quantitative Psychology at the University of Manitoba. She leads a data-driven analytics lab focused on developing and implementing advanced data analytics tools for diverse formats and structures in the social, behavioral, and health sciences. Her research employs a variety of statistical methods and computational algorithms, particularly in multivariate statistics, predictive modeling, and longitudinal data methods, to provide a foundation for meaningful and accurate decision-making. Sunmee's work is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and additional funding from the University of Manitoba. She is proficient in R and other statistical software including SAS, SPSS, and MATLAB, utilizing these tools for research, teaching, and student supervision. In 2023, she was appointed as a Research Affiliate at the Centre on Aging at the University of Manitoba, where her research aligns with the Centre’s focus on big data and predictive analytics in cognitive aging and late-life depression. Sunmee actively contributes to the academic community through collaborative research and the development of innovative statistical methods, exemplified by her GitHub projects and R package contributions.
Streams include Education, Administration, or Clinical.