Maria received her PhD in Statistics from the University of California, Santa Cruz, in 2014. Her dissertation research focused on developing Bayesian nonparametric modeling techniques for ordinal regression, which was further developed to handle ordinal regression relationships which evolve in discrete time. She also holds a bachelors degree in mathematical sciences from the University of California, Santa Barbara.
Maria is currently a statistician at RAND and was a postdoctoral researcher in the Department of Statistical Science at Duke University, as a member of the National Census Foundation -- Census Research Network (NCRN). The general goal of this group is to improve the way federal agencies analyze and disseminate data. She has focused on developing flexible multivariate imputation methods in order to fill in missing values in heterogeneous data, often arising from large-scale surveys. Another direction of research involves developing methodology for combining data from multiple sources.