I am a software engineer at Uber, where I work on mapping via computer vision and machine learning.

My previous work at Ibotta used machine learning to improve fraud detection, content personalization, and user churn. Prior to Ibotta I worked at Pivotal Labs, Automated Insights, and the Lawrence Livermore National Laboratory.

Personal interests include history, hiking, and Bayesian statistics. My graduate studies focused on Bayesian non-parametric approaches to machine learning and artificial intelligence. Most of my statistical work is done in Python, R, and Spark. For visualizations I often use libraries such as d3.

I have also taught introductory programming and data science courses at Duke University, Washington University, and University of Miami. I am a certified instructor with Software Carpentry and Data Carpentry and am available to teach workshops.

For additional information, including a copy of my résumé or CV, email me.