I received my M.S. and Ph.D. from Carnegie Mellon University. As an undergraduate, I attended Haverford College near Philadelphia, PA. At Haverford, I majored in Psychology, with a Math minor. Choosing a major was not easy, due to my diverse interests. In addition to Psychology and Math, I took several classes in Chemistry, Biology, and Foreign Languages.

Before beginning my graduate work, I was a member for Habitat for Humanity of Iredell County. I have had the distinct pleasure of taking part in almost every stage of construction from laying out a foundation to nailing in that last piece of baseboard in the bedroom closet.

I ran competitively for Haverford College, who won the NCAA 2010 national championship in cross-country. I still enjoy running for physical and psychological well-being. I am a fan of games of all shapes and sizes, from sports and card games to strategy, puzzle, and word games. As I suspect is true of many of my contemporaries, it was video games that first introduced me to the joys (and frustrations :) of programming.

Reading is another one of my hobbies. I recently finished *Les
Miserables*. If you enjoy the musical you will probably enjoy this
book immensely. You can read or skip the political diatribes according
to taste. I also recommend my two favorite books: *Catch-22* and
*The Count of Monte Christo*.

I use visual aids in a lot of my classes to help students understand important concepts. Here are some examples that I created using R.

My current research involves computational statistics and Bayesian non-parameteric processes. As part of my dissertation research, I developed theory of a graphical version of the famous Dirichlet Process. Graphical in this sense refers to a set of independence relationships among observed variables. I apply this theory to make inference about Bayesian mixture models under conditional independence constraints. By comparing the marginal likelihood of a set of data under various graphical models, I determine the relationship between variables from a mixture of distributions. I have written code for these two applications, which is available here. In addition to working with the graphical Dirichlet Process, I am interested in expanding the theory to other extensions and applications, including the Hierarchical Dirichlet Process of Teh, et al., and Pitman-Yor Processes. Graphical versions of the Beta Process are also particularly exciting.

It may be a cliché, but I am generally eager to learn about almost any topic. I have worked at various times as a teaching assistant in a chemistry lab, a research assistant in a cognitive psychology lab, and as a proof-reader and solutions-writer for a topology textbook. I hope to become more involved in interdisciplinary research in the near future, especially regarding cognition and linguistics.

- Curriculum Vitae (pdf)
- My Dissertation
- Thesis Defense - PDF using the LaTeX beamer class
- Source Code for Hyper Dirichlet Mixtures
- Visual Aids for Learning and Teaching Statistics
- Course Descriptions
- xkcd - Great mostly-scientific comic strip, including my favorite.
- slashdot.org - "News for Nerds", they often have interesting studies you can use for examples.