Rate My Professor Fang Yao

Fang Yao's research focuses on functional data analysis (FDA), particularly for sparse longitudinal data, high-dimensional data, nonparametric regression, and connections between longitudinal and functional data paradigms. His foundational contributions include interpretable models with complex correlation structures for improved inference in FDA. A landmark paper, "Functional data analysis for sparse longitudinal data" (Journal of the American Statistical Association, 2005, co-authored with H.-G. Müller and J.-L. Wang), has received over 2,100 citations. He has authored numerous influential publications and developed the PACE software package, widely used for functional data analysis. In recognition of his early-career achievements, he was awarded the CRM-SSC Prize in Statistics in 2014. Yao has mentored PhD students such as Hang Zhou (PhD PKU 2022, now Assistant Professor at UNC Statistics & Operations Research) and Yang Zhou (2022, Assistant Professor at Beijing Normal University School of Statistics). He holds editorial positions including Editor of the Canadian Journal of Statistics and past Associate Editor for the Annals of Statistics, Journal of the American Statistical Association, Statistica Sinica, and Journal of Computational and Graphical Statistics. With over 6,500 citations on Google Scholar, his work has profoundly impacted statistical methodology and applications across disciplines.