Alexander Volfovsky

Assistant Professor of Statistical Science

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Overview

I am interested in theory and methodology for network analysis, causal inference and statistical/computational tradeoffs and in applications in the social sciences. Modern data streams frequently do not follow the traditional paradigms of n independent observations on p quantities of interest. They can include complex dependencies among the observations (e.g. interference in the study of causal effects) or among the quantities of interest (e.g. probabilities of edge formation in a network). My research is concerned with developing theory and methodological tools for approaching such modern data structures by better understanding these underlying dependence structures. My work concentrates on better understanding Kronecker covariance structures as they are related to network analysis and high dimensional unbalanced factorial designs. I work on theory and methodology for high dimensional data as it relates to network analysis, causal inference and computational and statistical tradeoffs. My primary applied interest is in the health and social sciences with past and ongoing collaborations studying friendship formation in high schools, employment outcomes for college graduates and job mobility as a function of an underlying social network.

Education & Training

  • Ph.D., University of Washington 2013

  • B.Sc. (hons), University of Chicago 2009

  • M.S., University of Chicago 2009

QuBBD: Collaborative Research: Matching Methods for causal inference: big data and networks awarded by National Institutes of Health (Principal Investigator). 2017 to 2020

Ogburn, EL, and Volfovsky, A. "Networks." Handbook of Big Data. Ed. P Bühlmann, P Drineas, M Kane, and MJVD Laan. Chapman and Hall/CRC, 2016. 171-190.

Volfovsky, A, and Airoldi, EM. "Sharp total variation bounds for finitely exchangeable arrays." Statistics & Probability Letters 114 (July 2016): 54-59. Full Text Open Access Copy

Volfovsky, A, and Hoff, PD. "Testing for nodal dependence in relational data matrices." Journal of the American Statistical Association 110.511 (January 2015): 1037-1046. Full Text

Volfovsky, A, and Hoff, PD. "HIERARCHICAL ARRAY PRIORS FOR ANOVA DECOMPOSITIONS OF CROSS-CLASSIFIED DATA." The annals of applied statistics 8.1 (March 2014): 19-47. Full Text

Hoff, P, Fosdick, B, Volfovsky, A, and Stovel, K. "Likelihoods for fixed rank nomination networks." Network science (Cambridge University Press) 1.3 (December 2013): 253-277. Full Text

HOFF, PETER, FOSDICK, BAILEY, VOLFOVSKY, ALEX, and STOVEL, KATHERINE. "Likelihoods for fixed rank nomination networks." Network Science 1.03 (December 2013): 253-277.

Hollenbach, FM, Bojinov, I, Minhas, S, Metternich, NW, Minhas, S, Ward, MD, and Volfovsky, A. "Principled Imputation Made Simple: Multiple Imputation Using Gaussian Copulas."

Volfovsky, A, Airoldi, EM, and Rubin, DB. "Causal inference for ordinal outcomes."

Pages