Jinchi Lv  
 
 

Jinchi Lv

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

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


jinchilv (at) marshall.usc.edu
Office: BRI 400A
Phone: (213) 740-6603
Fax: (213) 740-7313

 

Short bio [CV]

Jinchi Lv is McAlister Associate Professor in Business Administration in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California, and an Associate Fellow of USC Dornsife Institute for New Economic Thinking (INET). He received his Ph.D. in Mathematics from Princeton University in 2007. His research interests include high-dimensional statistics, big data problems, statistical machine learning, neuroscience and business applications, and financial econometrics.

His papers have been published in journals in statistics, economics, information theory, biology, and computer science, and one of them was published as a Discussion Paper in Journal of the Royal Statistical Society Series B (2008). He serves as an associate editor of the Annals of Statistics (2013-present) and Statistica Sinica (2008-present). He is the recipient of the Royal Statistical Society Guy Medal in Bronze (2015), NSF Faculty Early Career Development (CAREER) Award (2010), USC Marshall Dean's Award for Research Excellence (2009), and Zumberge Individual Award from USC's James H. Zumberge Faculty Research and Innovation Fund (2008).


 
Representative Publications
  • Ren, Z., Kang, Y., Fan, Y. and Lv, J. (2016). Tuning-free heterogeneity pursuit in massive networks. Manuscript. [PDF]
  • Fan, Y., Kong, Y., Li, D. and Lv, J. (2016). Interaction pursuit with feature screening and selection. Manuscript. [PDF]
  • Fan, Y. and Lv, J. (2016). Innovated scalable efficient estimation in ultra-large Gaussian graphical models. The Annals of Statistics, to appear. [PDF]
  • Lv, J. and Liu, J. S. (2014). Model selection principles in misspecified models. Journal of the Royal Statistical Society Series B 76, 141–167. [PDF]
  • Fan, Y. and Lv, J. (2013). Asymptotic equivalence of regularization methods in thresholded parameter space. Journal of the American Statistical Association 108, 1044–1061. [PDF]
  • Lv, J. (2013). Impacts of high dimensionality in finite samples. The Annals of Statistics 41, 2236–2262. [PDF]
  • Fan, J. and Lv, J. (2008). Sure independence screening for ultrahigh dimensional feature space (with discussion). Journal of the Royal Statistical Society Series B 70, 849–911. [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]