In the SRP Extension, economics students test their summer models against real-world data, film students push a screenplay toward a short they can actually shoot, and future founders turn an idea into a pitch deck. It is where a paper finished in Seoul becomes the start of something longer.
The 2025 Seoul Research Program (SRP) ran from July 28 to August 7. When it ended, many students kept working with their professors through the Extension, a follow-on research and internship track that develops the topic each student explored over the summer. It is more than extra class time. Each track is designed by its professor, whether that means advanced research, paper refinement, an industry internship or a creative project, and each one ends in finished work. The relationship with the professor that began during SRP also becomes closer and more sustained.
Summer program and Extension, side by side
| Seoul Research Program | SRP Extension | |
|---|---|---|
| Grades | 9–12 | 9–12 |
| Stage | The regular summer program: intensive, hands-on research | The advanced stage that follows the summer program |
| How it works | Students work in person with faculty from leading universities and write a paper with the professor | Students continue research with the professor and mentors, building on the topic from the summer program |
| What it produces | One completed research paper | An advanced research project, an industry internship or a startup |
The five tracks in 2025
Economics with Ryan Fang (University of Chicago)
Professor Fang's Extension takes the economics paper students completed over the summer and brings it into contact with real data. At SRP, students learned how to build a model. Now they find out how that model works in the world.
Students either test their model against real data or develop it into a more rigorous mathematical structure. A model of consumer behavior or a political campaign, for instance, might be checked against social media sentiment data or election statistics. Fang stresses the reasoning that connects theory to evidence and teaches students that research is a matter of proof, not assumption. TAs help with data cleaning, analysis and visualization in Stata, R and Python, bringing the paper up to the standard of an academic conference.
