I am an Assistant Research Professor in the Duke Department of Political Science and Social Science Research Institute (SSRI), where I study a range of topics related to political accountability, including gerrymandering, social networks, election administration, and race and incarceration. My peer-reviewed work can be found in a range of journals, including APSR, Political Analysis, QJPS, PSRM, and the Election Law Journal. 

I am also the Director of the Duke Master in Interdisciplinary Data Science (MIDS) program, the current MIDS Director of Graduate Studies, and an Associate Director of the Rhodes Information Initiative at Duke.

I am passionate about empowering students of all backgrounds to use data science tools to solve real-world problems. To that end, I teach two courses in the first-year MIDS curriculum. Practical Data Science (IDS 720), a flipped-classroom, exercise-focused course designed to give students practical experience wrangling and analyzing messy, real-world data using the tools of a professional data scientist. Causal Inference & Solving Real Problems with Data (IDS 701), a course that teaches methods for answering causal questions and transitioning from doing well-scaffolded classroom exercises to solving messy, real-world problems. I also teach a Computational Methods for Social Scientists bootcamp each year for incoming social science graduate students from Political Science and Sociology.

Based on lessons learned teaching those courses, I’ve also co-developed a five-course Coursera Specialization on data science programming with my colleagues Kyle Bradbury, Drew Hilton, and Genevieve Lipp—Programming for Python Data Science: Principles to Practice—and am developing an intermediate data science textbook on critical thinking and problem solving.

Email: [email protected]