Department: Statistics, College of Arts and Sciences
COP: Computational Health and Life Sciences, Computational Social Sciences, Foundations of Data Science & AI
Interests: My research is at the intersection of applied, computational, and methodological statistics. I have been mostly working on Bayesian modeling and methods, with a focus on Bayesian nonparametrics, models for latent variables, and model assessment. Part of my work is dedicated to the inclusion of domain knowledge in the modeling framework. I am also interested in the development of open-source statistical software, and I am an active collaborator to the nimble project, an R-based software for hierarchical models.