University of Southern California

Faculty Profiles

Faculty Finder

Jinchi Lv
Assistant Professor of Data Sciences and Operations

USC Marshall School of Business
Los Angeles, CA 90089-0808

Phone: 
213-740-6603
jinchilv@marshall.usc.edu
Education: 
PhD, Princeton University; MS, BS, University of Science and Technology of China
Personal Website: 
http://www-bcf.usc.edu/~jinchilv

Overview

Jinchi Lv's research interests include high dimensional statistical inference, variable selection and machine learning, financial econometrics, and nonparametric and semiparametric methods. His papers have been published in the Annals of Statistics, Journal of the Royal Statistical Society Series B, Statistica Sinica, Journal of Econometrics, and Journal of Financial Econometrics. He serves as an associate editor of Statistica Sinica since 2008. He is the recipient of National Science Foundation CAREER Award, National Science Foundation Grant, 2008 Zumberge Individual Award from USC's James H. Zumberge Faculty Research and Innovation Fund, and 2009 Dean's Award for Research Excellence.

Research

Model selection principles in misspecified models • 2013
Asymptotic properties for combined L1 and concave regularization • 2013
Asymptotic equivalence of regularization methods in thresholded parameter space • 2013
High-dimensional thresholded regression and shrinkage effect • 2013
High-dimensional sparse additive hazards regression • 2013
Impacts of high dimensionality in finite samples • 2013
Stable oracle model and its recovery in misspecified models • 2013
Nonconcave penalized likelihood with NP-dimensionality • 2011
Sparse high-dimensional models in economics (invited review article) • 2011
A selective overview of variable selection in high dimensional feature space (invited review article) • 2010
Comments on: L1-penalization for mixture regression models • 2010
A unified approach to model selection and sparse recovery using regularized least squares • 2009
DASSO: connections between the Dantzig selector and Lasso • 2009
A unified approach to model selection and sparse recovery using regularized least squares • 2009
Sure independence screening for ultrahigh dimensional feature space (with discussion) • 2008
Rejoinder: Sure independence screening for ultrahigh dimensional feature space • 2008
High dimensional covariance matrix estimation using a factor model • 2008
Discussion: The Dantzig selector: statistical estimation when p is much larger than n • 2007
Aggregation of nonparametric estimators for volatility matrix • 2007
High dimensional variable selection and covariance matrix estimation (Ph.D. dissertation) • 2007