Forrest W. Crawford bio photo

Forrest W. Crawford

Assistant Professor
Biostatistics, Operations, EEB
Yale University

(203) 785-6125
60 College St LEPH Rm 207
PO Box 208034 New Haven CT 06510


Forrest W. Crawford is an Assistant Professor of Biostatistics, Operations, and Ecology & Evolutionary Biology at Yale University. He is affiliated with the Center for Interdisciplinary Research on AIDS, the Institute for Network Science, the Computational Biology and Bioinformatics Program, and the Public Health Modeling Concentration.

Research: mathematical and statistical problems related to discrete structures and stochastic processes in epidemiology, public health, biomedicine, and evolutionary science.

Methodological interests: networks and graphs, stochastic processes, semi-parametric inference, causal inference, computational statistics, optimization, and algorithms.

Practical applications: public health, infectious disease epidemiology, sociology, evolution and ecology, and genetics.

Funding: I am grateful for support from the Big Data to Knowledge (BD2K) program via the NIH Director’s New Innovator Award (DP2). Project page.

Job openings: Several postdoctoral fellowship positions are available. Current Yale students and applicants interested in joining the group should contact me by email.

Selected recent articles

  1. Aronow, P.M., Forrest W. Crawford and Zubizarreta, J.R. (2016) Confidence intervals for means under constrained dependence. Submitted. [link]
  2. Forrest W. Crawford (2016) The graphical structure of respondent-driven sampling. Sociological Methodology, 46, 187–211. [link]
  3. Forrest W. Crawford, Aronow, P.M., Zeng, L. and Li, J. (2015) Identification of homophily and preferential recruitment in respondent-driven sampling. Submitted. [link]
  4. Forrest W. Crawford, Wu, J. and Heimer, R. (2015) Hidden population size estimation from respondent-driven sampling: a network approach. Submitted. [link]
  5. Forrest W. Crawford, Minin, V.N. and Suchard, M.A. (2014) Estimation for General Birth-Death Processes. Journal of the American Statistical Association, 109, 730–747. [link]

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