My teaching draws on my interdisciplinary training in political science, data analysis, and network science. I am prepared to teach a wide range of undergraduate and graduate courses, including International Relations, International Political Economy, International Organizations and Global Governance, East Asian Politics, Political Networks, Big Data Analysis, and Research Methods. At Indiana University, I have served twice as Instructor of Record and completed seven semesters as an Associate Instructor, gaining experience working with diverse student populations and instructional formats.
My teaching philosophy emphasizes structured, incremental learning and the cultivation of an inclusive classroom environment. I design courses that progressively build skills from conceptual foundations to applied analysis, integrating qualitative political reasoning with quantitative and computational approaches. To support student engagement and learning assessment, I regularly employ interactive tools such as `TopHat` to encourage active participation, check students’ understanding in real time, and reinforce key concepts introduced in class. My teaching is further informed by policy engagement with the Taiwanese government, think tanks, and APEC, as well as my work as a Graduate Research Assistant examining Taiwan’s foreign relations with China, Japan, and the United States.
Click here to view my full teaching statement. Below is an overview of the courses I have taught as Instructor of Record and Associate Instructor at Indiana University Bloomington. Sample slides from my Instructor-of-Record course are provided below.
Data is big, and data is everywhere. In a world increasingly shaped by data—much of it about ourselves—being able to understand, interpret, and communicate data has become an essential skill. Data Fluency introduces students to the fundamental skills needed to navigate and make sense of data in the 21st century, including understanding data, extracting insight from data, generating predictions, and presenting data effectively. Drawing on concepts from Informatics and Data Science, this course emphasizes both practical skills and critical thinking. By the end of the course, students who successfully complete Data Fluency will be able to:
Global governance refers to the collective processes through which states, international organizations, and non-state actors coordinate decision-making to address issues that extend beyond national borders. These challenges—ranging from human rights protection and environmental sustainability to economic stability and international security—cannot be effectively managed by individual states alone. As global interdependence deepens, global governance has become increasingly complex, characterized by dense institutional networks, overlapping rules and policies, diverse interests and power relations, and the evolving nature of transnational problems.
This course examines the changing architecture of global governance. While traditionally shaped by state-created intergovernmental organizations (IGOs), global governance has transformed significantly in recent decades. Today, non-governmental organizations (NGOs), public–private partnerships, regime complexes, and private regulatory actors play an increasingly prominent role. The course invites students to critically assess the forces driving this diversification. Are these institutional innovations proactive solutions or responses to persistent global crises? Do they enhance the effectiveness and legitimacy of global governance, or introduce new challenges of coordination and accountability?
By the end of the course, students will acquire a foundational understanding of global governance and develop informed perspectives on its evolving structures and debates. The course also aims to cultivate sustained interest in global governance and encourage students to engage with international affairs as informed citizens, practitioners, or future researchers.
Due to a limited response rate (4.3%, n = 1 out of 23), selected comments are shared as illustrative feedback.
📄 Course Syllabus (PDF) 📝 Teaching Evaluation (PDF)
- “The instructor is extremely approachable and kind. He has been more than generous in accommodating summer schedules.”
- “I also appreciated that the instructor was transparent about learning alongside students when discussing emerging research.”