Inference for high-dimensional data: "large p small n" problems, covariance estimation, dimensionality reduction, classification. Applications to wireless sensor networks, computer vision, spectroscopy, remote sensing, gene array data.
Education
B.A. equivalent Mathematics: St. Petersburg State University, Russia, 1994
M.S. Mathematics, University of Utah, 1997
Ph.D. Statistics, University of California, Berkeley, 2002
Selected Publications
Bickel, P.J. and Levina, E. (2008). Regularized estimation of large covariance matrices. To appear in the Annals of Statistics.
Katenka, N., Levina, E., and Michailidis, G. (2007). Local Vote Decision Fusion for Target Detection in Wireless Sensor Networks. To appear in IEEE Transactions on Signal Processing.
Levina, E., Wagaman, A.S., Callender, A.F., Mandair, G.S., and Morris, M.D. (2007). Estimating the number of pure chemical components in a mixture by maximum likelihood. Journal of Chemometrics, 21(1-2):24--34.
Levina, E. and Bickel, P. J. (2006). Texture synthesis and non-parametric resampling of random fields. Annals of Statistics 34(4):1751-1773.
Bickel P.J. & Levina E. (2004) Some theory for Fisher's linear discriminant function,``naive Bayes'', and some alternatives when there are many more variables than observations. Bernoulli 10(6):989-1010.