Statistics expert witness has over 25 years of experience within the field of statistics, with areas of interest that include applied statistical modeling, categorical data analysis, mathematical statistics, multivariate data analysis, nonparametric methods, probability theory, sampling techniques, statistical methods, and statistical software. They hold a Ph.D. in Statistics, a master’s degree in Statistics, and a bachelor’s degree in Mathematics, with doctoral research focused on nonparametric Bayesian density estimation with intrinsic autoregressive priors. Their current academic leadership includes directing a center for applied statistics and data analysis, and their prior academic administrative experience includes undergraduate statistics program oversight within a statistics department.

For matters requiring statistical evaluation, their background supports objective analysis of study design, data interpretation, categorical and multivariate data, sampling methods, nonparametric techniques, public health research data, health science data, and statistical software use. Their professional record includes grant-funded and grant-support statistical work involving NIH, CDC, NSF, and related research programs, as well as publications and presentations tied to healthcare, public health, epidemiologic, medical, veterinary, and social science data. Their professional involvement includes the American Statistical Association, Caucus for Women in Statistics and Data Science, Women in Statistics in Korea, Korean-American Scientists and Engineers Association, Korean International Statistical Society, journal review activity, editorial board activity, mentoring, planning committee work, and governance-related service in statistics and public health fields.

They have applied their statistical skills within behavioral science, environmental health, health science, medical, public health, psychology, and social science fields. Their work also includes 13 years of non-litigation consulting experience, including grant support and general statistical support for research involving nursing, public health, medicine, veterinary medicine, social work, psychology, health sciences, natural resources, nutrition and exercise science, and related fields. Their applied and instructional background includes statistical methods in the health sciences, statistical software and data analysis, applied statistical models, categorical data analysis, sampling techniques, nonparametric methods, applied multivariate data analysis, experimental design, mathematical statistics, and probability theory.