I have served as Teaching Fellow (Yale) or Graduate Student Instructor (Berkeley) for these courses:

  • Introduction to International Relations

    Fall 2020, Graduate Student Instructor, Berkeley.

    This course surveys major theoretical approaches to international politics, using these approaches to assess historical and contemporary events.

  • Conflict, Security, and Political Psychology

    Spring 2020, Graduate Student Instructor, Berkeley

    This course explores international and sub-national conflict and security issues from the perspective of different frameworks of political psychology. Students will then use the frameworks to examine historical and contemporary questions in international politics.

  • WAR!

    Fall 2019, Head Graduate Student Instructor, Berkeley

    This course seeks to answer these and other questions surrounding the phenomenon of war. By examining the details of specific conflicts, students will understand the dynamics that affect the onset, duration, and cessation of both interstate and intrastate conflicts.

  • civil conflict and international intervention

    Spring 2019, Graduate Student Instructor, Berkeley

    This course explores why, and to what end, civil conflicts are fought. Students use theoretical international security approaches to assess when and why international actors intervene in ongoing conflicts or to resolve post-conflict tensions.

  • dictatorship and its discontents

    Fall 2018, Graduate Student Instructor, Berkeley

    This course explores the characteristics and dynamics of non-democratic regimes: how and why they come about, what sustains them, why some people resist them and others do not, and how and why they decline and fall.

  • applied quantitative analysis

    Fall 2015 and Spring 2016, Teaching Fellow, Yale

    This course is an introduction to statistics and their application in public policy and international affairs research. Specifically, the course covers issues related to data collection (including surveys, sampling, and weighted data), data description (graphical and numerical techniques for summarizing data), probability and probability distributions, confidence intervals, hypothesis testing, measures of association, and regression analysis.