I am a postdoctoral associate in the Crawford Lab at Yale School of Public Health in the department of Biostatistics. I received my Ph.D. in Statistics from the University of Minnesota on June 9th, 2017. My dissertation (view here) was advised by Charles J. Geyer and R. Dennis Cook. I graduated from Southern Illinois University in Carbondale, IL with a BS in mathematics and a minor in economics.
I am interested in a wide variety of disciplines within Statistics. These include, but are not limited to, maximum likelihood estimation, exponential family theory, generalized linear models, envelope methodology, conformal prediction, causal inference, bootstrap techniques, and the tradeoff between robustness and efficiency in estimation. My CV is attached here.
My research mission is to improve statistics methodologies that are applicable to real-world problems. My focus is placed on both the theoretical and computational aspects of this methodology. To better understand relevant real-world problems, I work closely with scientists and researchers across a variety of disciplines. Writing technical research papers, or an accompanying technical report, that can be understood by the intended scientific audience is central to my research mission. Current methodological work of mine has applications in evolutionary biology, engineering, epidemiology, chemometrics, and several domains of physics.