Elizabeth Schifano, PhD

Assistant Professor
University of Connecticut
Department of Statistics
215 Glenbrook Road, Unit 4120
(Austin Building, AUST)
Storrs, CT 06269-4120
Office: (860) 486-6143
Cell: (716) 479-0223

Center for Health, Intervention, and Prevention
2006 Hillside Road, Unit 1248
(Ryan Building, JRB)
Storrs, CT 06269-1248
Office: (860) 486-5079
Email: elizabeth.schifano@uconn.edu

Research Overview

Motivated by high-dimensional genomic data applications, my methodological research focuses on two main areas: variable selection via penalized regression models and powerful model-based inference. My involvement in collaborative research has expanded my interests in related areas of environmental genomics and health. My most recent collaborative projects include a longitudinal investigation of lung disease in cotton textile workers and a multivariate investigation of genetic markers related to smoking behavior.


Postdoctoral Research Fellow, 2010 - 2012, Harvard School of Public Health
Ph.D. Statistics, 2010, Cornell University
M.S. Statistics, 2007, Cornell University
B.S. Biometry and Statistics, Summa Cum Laude, 2004, Cornell University

Featured Publications

Bar, H.Y. and Schifano, E.D. (2011). Empirical and Fully Bayesian Approaches for Random Effects Models in Microarray Data Analysis. Statistical Modelling, 11(1), 71-88.

Schifano, E.D., Strawderman, R.L., and Wells, M.T. (2010). Majorization-Minimization Algorithms for Nonsmoothly Penalized Objective Functions. Electronic Journal of Statistics, 4, 1258-1299.

Bar, H.Y., Booth, J.G., Schifano, E.D., and Wells, M.T. (2010). Laplace Approximated EM Microarray Analysis: An Empirical Bayes Approach for Comparative Microarray Experiments. Statistical Science, 25(3), 388-407.

Figueroa, M.E., Lugthart, S., Li, Y., Erpelinck-Verschueren, C., Deng, X., Christos, P.J., Schifano,E.D., Booth, J.G., van Putten, W., Skrabanek, L., Campagne, F., Mazumdar, M., Greally, J.M., Valk, P.J., Lowenberg, B., Delwel, R., and Melnick, A. (2010). DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia. Cancer Cell, 17, 13-27.

Bar, H.Y. and Schifano, E.D. (2009). Bayesian Approaches for Random Effects Models in Microarray Analysis. Proceedings of the 24th International Workshop on Statistical Modelling.

Gaile, D.P., Schifano, E.D., Miecznikowski, J.C., Java, J.J., Conroy, J.M., and Nowak, N.J. (2007). Estimating the Arm-Wise False Discovery Rate in Array Comparative Genomic Hybridization Experiments. Statistical Applications in Genetics and Molecular Biology: Vol. 6 : Iss. 1, Article 32. Available at: http://www.bepress.com/sagmb/vol6/iss1/art32.

*Last Revised: 2013-07-26 15:45:31