Hi, I’m a PhD Candidate in Statistical Science at Duke University. I’m working with Prof. Mike West and 84.51 on forecasting daily grocery store sales for thousands of items. I’m developing efficient Bayesian time series models to tackle this high-dimensional problem, along with a Python Package for standard dynamic generalized linear models (DGLMs). My previous project with Prof. Mike West and Michael Lindon is Adaptive Variable Selection. We developed a strategy for time-adaptive model combination and forecasting, targeted at a specific objective.
In the summer of 2018, I worked as a Machine Learning and Relevance Intern at LinkedIn. I contributed to the ranking algorithm for content in the LinkedIn Feed, and specifically to an intiative which provides attention to lesser known LinkedIn members. I built predictive models for clicks, likes, and comments in Spark and Scala, and a multi-objective optimization routine in R.
Prior to graduate school, I lived in Philadelphia, working for Thorogood as a Business Intelligence Consultant. I helped to design and build a suite of interative Tableau dashboards for a multinational consumer packaged goods company.
In 2014, I received my bachelors from Lafayette College in Easton, PA, with a dual degree in Mathematics and Chemical Engineering.
Apart from Statistics, I enjoy reading, learning about history, and playing games of all types. I’m an avid Bridge player, along with many board games and sports.