My teaching is guided by a simple principle: students learn best when they connect substantive political questions to concrete analytical practice. Drawing on my interdisciplinary training in political science, informatics, data analysis, and network science, I design courses that help students build strong foundations in political inquiry while also developing the analytical tools needed to evaluate evidence, communicate arguments clearly, and conduct independent research.
At Indiana University, I have served twice as Instructor of Record and completed seven semesters as an Associate Instructor, teaching across Political Science and Informatics in courses such as Politics of Global Governance, Data Fluency, International Organization, Analyzing Politics, and Introduction to Informatics. I have also taught R at Indiana University through a hands-on crash course introducing students to data import, manipulation, analysis, and visualization. My teaching emphasizes structured, incremental learning, inclusive engagement, and hands-on practice, using discussion, project-based assignments, and low-stakes active-learning tools such as TopHat. It is also shaped by my experience teaching in Taiwan and by prior policy-oriented work with the Taiwanese government, think tanks, and APEC, which helps me connect classroom learning to real political and policy problems.
Student feedback has consistently highlighted my clarity, approachability, and ability to connect course material to real-world examples. Click here to view my general teaching statement. Below is an overview of the courses I have taught at Indiana University Bloomington, along with sample course materials and teaching evaluations.
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.”