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Michael Rosenblum holds a PhD in Applied Mathematics from the Massachusetts Institute of Technology. Prior to joining the Biostatistics faculty at Johns Hopkins University as an Assistant Professor, he was a postdocoral researcher in statistics and biostatistics at the University of California’s Berkeley and San Francisco campuses, under the mentorship of Professor Mark van der Laan. Michael’s research is in the statistical areas of design and analysis of randomized trials, causal inference, and survey sampling; it is driven by concrete applications including the Methods for Improving Reproductive Health in Africa trial of a new HIV prevention method, the Research in Access to Care for the Homeless study of HIV positive individuals, and a recent re-analysis of data from a survey of mortality in Iraq. He plans research to address the FDA’s Critical Path Initiatives to develop innovative trial designs, help determine which drug regimens give the best chance of survival to HIV positive individuals with adherence challenges, and improve reliability in cluster sampling surveys. Michael also has valuable experience with data communications systems tailored to less developed country environments, through his work with the Technology and Infrastructure for Emerging Regions project at the University of California, Berkeley. Papers: Rosenblum, M. and van der Laan, M., September, 2009 Using Regression Models to Analyze Randomized Trials: Asymptotically Valid Hypothesis Tests Despite Incorrectly Specified Models. Biometrics, Volume 65, Issue 3, pages 937-945 Rosenblum, M., Jewell, N. P., van der Laan, M. J., Shiboski, S., van der Straten, A., and Padian, N. Analyzing Direct Effects in Randomized Trials with Secondary Interventions: An Application to HIV Prevention Trials. Journal of the Royal Statistical Society, Series A, (Statistics in Society), Volume 172, Number 2, April 2009, pp. 443-465(23)
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