Education: I have been a PhD student in the Department of Statistics at Carnegie Mellon University since August 2010. I received a Master’s in Statistics from Carnegie Mellon in May 2011. Before that, I received a Bachelor’s degree from Carnegie Mellon in May 2010, double-majoring in Computational Finance and Statistics.
Research: Currently, I am working on several different research projects:
- Disambiguating USPTO Inventors with Classification Models Trained on Comparisons of Labeled Inventor Records
- Improving NHL Player Ability Ratings with Regularization and Hazard Function Models for Goal Scoring and Prevention
- Statistical Record Linkage in the United States Census
- Predicting NBA Game Outcomes
Teaching: For the second straight summer, I taught 36-217 Probability Theory and Random Processes. This course provides an introduction to probability theory and is designed for students in Electrical and Computer Engineering. Topics include elementary probability theory, conditional probability and independence, random variables, distribution functions, joint and conditional distributions, limit theorems, Poisson processes, and Markov chains.