Sara Wade joined the group as a Research Associate (Postdoc) in November 2012. She received a B.Sc. in Mathematics at the University of Maryland, College Park. In January 2013, she is expected to earn her PhD in Statistics from Bocconi University in Milan, where she worked on Bayesian nonparametric regression with Professor Sonia Petrone.
Her research interests include regression; density estimation; conditional density estimation; mixture models; clustering; predictive and theoretical properties of Bayesian regression models; random probability measures and dependent random probability measures; Markov Chain Monte Carlo methods; and Bayesian nonparametrics and statistics in general.
Wade S., Walker S. G., and Petrone S. (2012). “A predictive study of Dirichlet process mixture models for curve fitting.” Submitted.
Antoniano Villalobos I., Wade S., and Walker S. G. (2012). “A nonparametric regression model for the study of hippocampal atrophy in Alzheimer’s Disease.” Submitted.
Wade S., Mongelluzzo S., and Petrone S. (2011). “A enriched conjugate prior for Bayesian nonparametric inference.” Bayesian Analysis 6: 359-386. pdf