Yingying Fan  
 
 

Yingying Fan

Professor of Data Sciences and Operations
Dean's Associate Professor in Business Administration
Data Sciences and Operations Department
Marshall School of Business
University of Southern California
Los Angeles, CA 90089

Professor of Economics and Computer Science
University of Southern California

Associate Fellow
USC Dornsife Institute for New Economic
Thinking (INET)

fanyingy (at) marshall.usc.edu
Office: BRI 307B
Phone: (213) 740-9916
Fax: (213) 740-7313
 

Short bio

Yingying Fan is Professor and Dean's Associate Professor in Business Administration in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California, Professor in Departments of Economics and Computer Science at USC, and an Associate Fellow of USC Dornsife Institute for New Economic Thinking (INET). She received her Ph.D. in Operations Research and Financial Engineering from Princeton University in 2007. She was Lecturer in the Department of Statistics at Harvard University from 2007-2008. Her research interests include statistics, data science, machine learning, economics, big data and business applications, and artificial intelligence and blockchain.

Her papers have been published in journals in statistics, economics, computer science, and information theory. She is the recipient of Fellow of Institute of Mathematical Statistics (2020), Fellow of American Statistical Association (2019), NIH R01 Grant (2018), the Royal Statistical Society Guy Medal in Bronze (2017), USC Marshall Dean's Award for Research Excellence (2017), the USC Marshall Inaugural Dr. Douglas Basil Award for Junior Business Faculty (2014), the American Statistical Association Noether Young Scholar Award (2013), NSF Faculty Early Career Development (CAREER) Award (2012), Zumberge Individual Award from USC's James H. Zumberge Faculty Research and Innovation Fund (2010), and USC Marshall Dean's Award for Research Excellence (2010), as well as a Plenary Speaker at the 2011 Institute of Mathematical Statistics Workshop on Finance, Probability, and Statistics held at Columbia University. She has served as an associate editor of Journal of the American Statistical Association (2014-present), Journal of Econometrics (2015-2018), Journal of Business & Economic Statistics (2018-present), The Econometrics Journal (2012-present), and Journal of Multivariate Analysis (2013-2016).

  
Representative Publications
  • Fan, Y., Demirkaya, E., Li, G. and Lv, J. (2020). RANK: large-scale inference with graphical nonlinear knockoffs. Journal of the American Statistical Association 115, 362-379. [PDF]
  • Fan, Y., Demirkaya, E. and Lv, J. (2019). Nonuniformity of p-values can occur early in diverging dimensions. Journal of Machine Learning Research 20, 1-33. [PDF]
  • Candès, E. J., Fan, Y., Janson, L. and Lv, J. (2018). Panning for gold: 'model-X' knockoffs for high dimensional controlled variable selection. Journal of the Royal Statistical Society Series B 80, 551-577. [PDF]
  • Fan, Y., Kong, Y., Li, D. and Zheng, Z. (2015). Innovated interaction screening for high-dimensional nonlinear classification. The Annals of Statistics 43, 1243-1272. [PDF]
  • Fan, Y. and Tang, C. (2013). Tuning parameter selection in high dimensional penalized likelihood. Journal of the Royal Statistical Society Series B 75, 531-552. [PDF]
  • Fan, Y. and Li, R. (2012). Variable selection in linear mixed effects models. The Annals of Statistics 40, 2043-2068. [PDF]
  • Fan, J. and Fan, Y. (2008). High-dimensional classification using features annealed independence rules. The Annals of Statistics 36, 2605-2637. [PDF]
  • Fan, J., Fan, Y. and Lv, J. (2008). High dimensional covariance matrix estimation using a factor model. Journal of Econometrics 147, 186-197. [PDF]