My teaching seeks to help students understand what it means to think and work as a sociologist: how to formulate questions about the social world, what theory and methods allow us to pursue those questions, and how sociological knowledge can be meaningful both within and beyond the discipline. As new technologies such as artificial intelligence reshape how students learn and use knowledge, I also see it as part of my responsibility to help students use these tools thoughtfully while preserving the development of their own knowledge and reasoning.

Future teaching interests

My research and teaching interests span several areas, including sociological theory, education and stratification, family demography, and quantitative methods ranging from introductory statistics to machine learning and causal inference. I am prepared to teach these subjects at both the undergraduate and graduate levels.

Teaching is also an important way in which I continue to learn as a sociologist: across my courses, I have sought to share how I understand the core interests of sociology and how sociological questions can be pursued through theory and empirical inquiry, while continually reflecting on what defines sociological knowledge, how we produce it, and why it matters. I look forward to continuing this process of learning alongside my students, and to considering together what makes sociological knowledge meaningful both within and beyond the discipline.

Courses

SOC 301

Statistical Methods in Sociology

An introductory course fulfilling the quantitative methods requirement, designed for students with varying levels of mathematical preparation. Taught by Professor Tod G. Hamilton; I served as Assistant Instructor for two semesters.

Teaching responsibilities: I organized and facilitated review sessions focused on course materials and statistical concepts. I also held office hours to answer questions and provide additional support to students.

  • "Ha–Joon's comments on the assignments were generally very helpful, especially when studying for the final! I appreciate that he pointed out areas we went wrong."
  • "VERY helpful supplement to lecture. Preceptor provided very thorough feedback and answers to questions."

SOC 302

Sociological Theory

A course examining major works and debates in sociological theory. Taught by Professor John N. Robinson III; I led weekly discussion sections.

Teaching responsibilities: I organized and facilitated discussion and debate sessions focused on the course material, including key theoretical concepts, theorists, and assigned readings. I also held office hours to provide additional opportunities for students to discuss course material and their assignment projects.

  • "Ha–Joon did a great job expanding upon the content covered in lecture, reviewing, clarifying, and expanding upon key concepts and theorists. Precept also had interesting conversations about the readings that expanded upon the theory we were learning."
  • "I liked Ha Joon a lot, I thought he did a great job getting us to engage with each other and him during precepts. He was super helpful in office hours and just generally kind."

SOC 306

Machine Learning with Social Data

An advanced methods course on machine learning applications to social science data, enrolling more than one hundred students across sociology, other social sciences, computer science, and engineering. Taught by Professor Brandon Stewart; I led weekly precept sections.

Teaching responsibilities: I developed weekly problem sets designed to provide hands-on practice with machine learning methods and facilitated weekly precept meetings focused on applying course concepts. I also held office hours to answer questions about the problem sets and course material.

  • "I felt like the assignments and problem sets were all really fair and actually helped me learn!"
  • "Precept assignments were helpful for learning and applying R!"
  • "Assignments are great, both weekly ones and major assignments. They are very good at guiding you through the material as the semester progresses."
  • "Loved the diversity in types of assignments – sometimes we would be practicing coding a certain ML model, other times we would be writing paragraphs critiquing a social science paper. The variety encapsulated the interdisciplinary nature of using ML with social data and I learned a lot from completing them."

Fall 2026 · Upcoming

Quantitative Methods for Sociology Graduate Students

A graduate-level statistics course, taught by Professor Brandon Stewart, covering foundational material from probability theory through the properties and diagnostics of linear regression, with a second half devoted to the use of agentic AI in data analysis and its caveats. I will serve as Assistant in Instruction.

Advising and College Life

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Since 2022, I have served as a Residential Graduate Student at Yeh College at Princeton, where I lived with and mentored 30–40 first-year undergraduates each year. This role has allowed me to advise students not only on course selection and major choice, but also on navigating the broader transition to university life. In addition to discussing academic goals, I have worked with students on balancing academic and personal commitments, managing the pressures of a demanding university environment, and identifying priorities that support their longer-term well-being and development.

I have also advised junior and senior students in thesis writing through a weekly writing bootcamp and advised students considering graduate school about academic and career pathways.