My research covers a variety of topics in statistics and data science, typically motivated by scientific questions in global health, economics, demography, and sociology. Recent projects include estimating features of social networks (e.g. the degree of clustering or how central an individual is) using data from standard surveys, inferring a likely cause of death (when deaths happen outside of hospitals) using reports from surviving caretakers, and quantifying & communicating uncertainty in predictive models for global health policymakers. More information about OpenVA, our suite of open tools to manage and analyze verbal autopsy surveys, is available here.

I’m the former Editor of the Journal of Computational and Graphical Statistics and a 2019 recipient of the NIH Director’s New Innovator Award. I was elected as a Fellow of the American Statistical Association in 2023.

An description of some of our work recently appeared in the Wall Street Journal and it was used for a visual story in the Washington Post.

Technical reports and working papers

Please see arXiv for the most up to date list of working papers.

• Robustly estimating heterogeneity in factorial data using Rashomon Partitions
• Valid inference using language model predictions from Verbal Autopsy narratives
• Non-robustness of diffusion estimates on networks with measurement error
• Bayesian analysis of verbal autopsy data using factor models with age- and sex-dependent associations between symptoms
• Do we really even need data?
• General covariance-based conditions for Central Limit Theorems with dependent triangular arrays
• Asymptotically normal estimation of local latent network curvature
• Feasible contact tracing
• The role of scaling and estimating the degree ratio in the Network Scale-up Method
• Dempster-Shafer P-values: thoughts on an alternative approach for multinomial inference
• Bayesian age category reconciliation for age- and cause-specific under-five mortality estimates
• Spectral goodness-of-fit tests for complete and partial network data (overview and code)
• Estimating spillovers using imprecisely measured networks (code)
• Verbal autopsy in civil registration and vital statistics: The Symptom-Cause Information Archive
• Smart containment with active learning: A proposal for a data-responsive and graded approach to COVID-19 (more details)
• Quantifying the contributions of training data and algorithm logic to the performance of automated cause-assignment algorithms for verbal autopsy
• Examining Racial Segregation in Associative Networks on Twitter

Affiliations

• University of Washington
  • Professor, Department of Statistics and Department of Sociology.
  • Core faculty member, Center for Statistics and the Social Sciences.
  • Senior Data Science Fellow, eScience Institute.
  • Research affiliate, Center for Studies in Demography and Ecology.
  • Faculty partner, Responsible AI Systems & Experiences (RAISE).