Yingying Fan is a Chinese-American statistician and Centennial Chair in Business Administration and Professor in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California.[1] She is currently the Associate Dean for the PhD Program at USC Marshall. She also holds joint appointments at the USC Dana and David Dornsife College of Letters, Arts and Sciences, and Keck Medicine of USC. Her contributions to statistics and data science were recognized by the Royal Statistical Society Guy Medal in Bronze in 2017[2] and the Institute of Mathematical Statistics Medallion Lecture in 2023.[3] She was elected Fellow of American Statistical Association in 2019[4] and Fellow of Institute of Mathematical Statistics for seminal contributions to high-dimensional inference, variable selection, classification, networks, and nonparametric methodology, particularly in the field of financial econometrics, and for conscientious professional service in 2020.[5]

Fan, along with her collaborators, has developed some popular statistical and data science tools including the generalized information criterion (GIC), the model-X knockoffs (MXK), the deep learning inference using knockoffs (DeepLINK), and the statistical inference on membership profiles in large networks (SIMPLE) as well as some fundamental asymptotic theory for the eigenvectors of large random matrices and high-dimensional random forests.

Some of her representative publications include:


  1. ^ "Yingying Fan | USC Marshall". www.marshall.usc.edu.
  2. ^ "RSS announces honours for 2017 | StatsLife". www.statslife.org.uk.
  3. ^ "Institute of Mathematical Statistics | Honored Special Awards & Lecturers Recipient List".
  4. ^ "The 2019 ASA Fellows" (PDF). Retrieved 2023-08-31.
  5. ^ "Institute of Mathematical Statistics | Congratulations to the 2020 IMS Fellows!".