I am a postdoctoral researcher at the Perelman School of Medicine at the University of Pennsylvania, working in the labs of Yong Chen and Mary Boland on statistical methodology and data mining algorithms for electronic health records (EHR). Before coming to Penn, I completed my PhD in Statistics in August 2018 at the University of Florida under the supervision of Malay Ghosh. I received my BA in Economics and Government from Cornell University in May 2007 and my MS in Applied Mathematics from the University of Massachusetts Amherst in May 2012. From June 2007-August 2010, I worked as a financial software analyst, and from June 2012-July 2014, I worked as a systems engineer.
For more information about me, please see my CV.
My research is broadly focused on developing flexible Bayesian methods and scalable algorithms for very high-dimensional data. My primary methodological and theoretical interests are:
In my applied work, I work on:
- high-dimensional Bayesian estimation and variable selection
- nonparametric/semiparametric models
- scalable Bayesian methods using optimization algorithms and approximate MCMC algorithms
- functional/longitudinal data analysis.
- bias reduction in meta-analysis
- spatial modeling of maternal health outcomes using data from electronic health records (EHR)
- distributed algorithms that aggregate patient-level data into succinct summary statistics while preserving patient privacy.