I'm drawn to questions of how much useful information can be extracted from difficult data. This puts me in and around the intersection of a few research areas including Bayesian analysis, partial identification, causal inference, measurement error, and evidence synthesis. Many of the motivations for, and applications of, my work arise in epidemiology, public health, and biostatistics.
You can check out recent courses on my teaching page.
Pleased to participate in the STRATOS initiative, focussed on STRengthening Analytic Thinking for Observational Studies. This initiative, which now boasts more than 100 members from 19 countries, is organized according to numerous many topics groups and panels. I work within the Topic Group on Measurement Error and Misclassification.
My research page includes preprints as well as published work, and links to code and supplementary materials. Or you can check my profile on Google Scholar.
Pleased to participate on the methods side of the multidisciplinary and international ReCoDID consortium, on the Reconciliation of Cohort Data in Infectious Diseases.
I'm fortunate to have worked with current and former graduate students and postdoctoral fellows.