My research focuses on genomics of pathogens, especially HIV-1, towards the goals of a prophylactic HIV-1 vaccine and a cure for HIV. I have contributed methods and analyses that have helped to shape the global efforts in these realms, specifically in “sieve analysis,” which looks to pathogen sequence variation across arms of a clinical trial for sensitive evidence of vaccine-induced immunity and for iterative evaluation of putative correlates of protection. This work is not limited to HIV-1; for instance I have been involved in several studies addressing other pathogens (HSV-2, dengue, TB, rotavirus). I am also a clinical trials statistician on multiple HIV-1 vaccine and prevention trials through the HIV Vaccine Trials Network, HIV Prevention Trials Network, HIV Microbicide Trials Network, the Gates Foundation‘s Coalition for AIDS Vaccine Discovery, and their new Global Health Vaccine Accelerator Program. I have a small research group at the Fred Hutch where I collaborate extensively with local statisticians with complementary expertise as well as with researchers around the globe.

My methodological foci are threefold. In basic statistical foundations I work with Art Dempster and a recently growing group of “BFFs” (Bayesian, Frequentist, and Fiducial) on methodological developments and applications of Dempster-Shafer theory. I have extensively developed methods and software for inferring parameters of profile hidden Markov models with particular interest in applications to nucleotide sequence families such as endogenous and exogenous viruses. Finally I have developed sieve analysis methods and am particularly interested in vaccine efficacy, correlates, and sieve analysis methodology that accounts for subject-level heterogeneity.