I have taught and served as a TA for undergraduate courses in Comparative Politics and International Relations, and served as a TA for graduate courses on Quantitative Methodology.
Introduction to Comparative Politics, Stony Brook University & UNC-Chapel Hill
Lead Instructor: Fall 2018, Fall 2019, Spring 2020, Fall 2020 & Fall 2022
Teaching Assistant: for Rahsaan Maxwell (Spring 2017) and Andrew Reynolds (Fall 2016)
This course introduces the important themes of Comparative Politics to undergraduate students. It is designed to familiarize students with the core themes and theories relevant to the study of politics around the world. The course also touches upon a few contemporary themes in comparative politics research. As instructor, I structure the course around developing writing skills for social science and regular student-led discussions. Please feel free to reach out about a recent syllabus.
Introduction to International Relations, UNC-Chapel Hill
Teaching Assistant: for Navin Bapat (Fall 2017 & Spring 2021)
This course introduces undergraduate students to some of the most important topics and puzzles in the study of international relations, as well as analytic concepts that can be used to study world politics.
Statistical Models, MA in Comparative and International Studies (MACIS) at ETH-Zürich
Teaching Assistant: for Dominik Hangartner & Moritz Marbach (Spring 2018 & Spring 2019)
This course provides a graduate-level introduction to statistical methods for modeling and prediction, including theoretical underpinning and practical applications. Topics include linear regression, classification, resampling, shrinkage, trees, support vector machines, and clustering.
Causal Inference, MA in Comparative and International Studies (MACIS) at ETH-Zürich
Teaching Assistant: for Dominik Hangartner & Dalston Ward (Spring 2018 & Spring 2019)
This course provides a graduate-level introduction to statistical methods used for causal inference, with an emphasis on the potential outcomes framework. Designs and methods related to observational and experimental data are covered, including randomization, matching, difference-in-differences, regression discontinuity, instrumental variables, and synthetic control methods.