Instructor of Record
- Causal Inference and Applications (Summer 2024, Undergraduate): Overall rating: 4.8 / 5.0; Enrollment: 47.
- Introduction to Comparative Politics (2022, 2023, 2024, Undergraduate): Overall rating: 4.7 / 5.0; Enrollment: ~120 per term.
Selected Teaching Assistant Experiences
- Corruption in Developing Countries (Winter 2023, Undergraduate): Overall rating: 4.7 / 5.0; Enrollment: 220.
- Analyzing Politics (Winter 2022, Undergraduate): Overall rating: 4.6 / 5.0; Enrollment: 55.
- Advanced Statistical Applications (Winter 2025, Graduate): Overall rating: 4.8 / 5.0; Enrollment: 20.
Teaching Approach
I teach quantitative and comparative politics with a focus on hands-on methods, transparent assessment, and practical research design. My courses are built around the principle that students learn best by actively doing—writing code, interpreting results, and critically evaluating empirical claims. I integrate statistical software such as R and Stata into the core of the curriculum, ensuring that students not only understand methodological concepts but can also implement them in replicable workflows.
I emphasize causal thinking as the foundation for both descriptive and inferential work, guiding students to identify credible identification strategies and to recognize the limits of each approach. Assignments are designed to simulate real-world research tasks, from data cleaning and visualization to pre-analysis planning and policy evaluation.
Assessment is transparent and criteria-based, with clear rubrics and frequent formative feedback. I make extensive use of structured office hours, during which students receive tailored guidance on coding, interpretation, and project design. I encourage collaborative problem-solving while maintaining rigorous standards of academic integrity and replicability. See Teaching Statement & full evaluations (PDF)