Summary
Shujie Ma is a Professor of Statistics at UC Riverside with a decade of academic experience translating advanced probability and asymptotic theory into practical tools for bioinformatics, genetics, medicine, and econometrics. Her methodological work focuses on non- and semi-parametric modeling for complex and high-dimensional data, simultaneous inference, and dimension reduction with strong grounding in empirical process theory and resampling techniques. She combines theoretical rigor with interdisciplinary collaboration, having partnered closely with biostatisticians and economists on both computational and theoretical projects. Known for tackling correlated, longitudinal, and time-series problems, she brings deep expertise in variable selection, measurement error, and mixed models to applied scientific questions. An academic who enjoys moving between theory and application, she uniquely blends extreme value and large-sample theory insights into practical inference for modern high-dimensional datasets.
9 years of coding experience
15 years of employment as a software developer
Ph.D., Statistics, Ph.D., Statistics at Michigan State University