Political Science PhD candidate focusing on American institutions




The Use of Social Science Computer Programs

In Fall 2016 I taught the introduction to social science computing course for first year Ph.D. students in the Political Science department. This course was an entry-level course in R programming, with a focus on data manipulation, cleaning and visualization.


Full Course Materials

In the Spring/Summer term of 2018 I was the instructor of record for POLSCI 111, Introduction to American Politics. This course used the The American Political System (Kollman 2017) and Readings in American Politics: Analysis and Perspectives (Kollman 2018) to introduces students to the foundations of American Politics.


Full Course Materials

POLSCI 111: 

Introduction to American Politics

UM Big Data Summer Camp

In the summer of 2019 I was an instructor for Big Data Summer Camp, at the University of Michigan, sponsored by the Interdisciplinary Committee on Organizational Studies and Michigan Institute for Data Science. This hands on, intensive week-long camp camp is collaboratively taught by graduate student instructors to over 70 graduate and faculty participants from more than 30 different disciplinary units on campus. The camp was taught entirely in python, and covered topics from database management, machine learning, to web-scraping, text processing and network analysis. I was the lead instructor for the network analysis lesson.

Introduction to Network Analysis in Python

Video of Network Introduction Session

Teaching Assistantships

GSI for PolSci 381 Research Design: Upper level writing seminar and honors sequence gateway in which undergraduates produced full research designs in preparation to propose honors theses.

GSI for Computational Social Science Initiative Methods Workshop - "Text as data" with Brandon Stewart.

Guest lecturer in Network Visualization in 470.673 Numbers, Pictures, Politics at Johns Hopkins Krieger School.