Five Questions with Yunhyoung Kim

Yunhyoung Kim is an assistant professor in the school’s Marketing and Business Law academic area. Before joining the KU School of Business faculty, Kim received his doctorate in industrial systems engineering from Yonsei University in South Korea before earning his doctorate in business administration from the University of Minnesota. Some of his research interests include reinforcement learning, digital marketplace, and quantitative behavioral modeling.  

What got you interested in your field, and what is the most rewarding part of being involved in it?  

I have always been interested in how people make decisions. Before entering academia, I worked at one of the largest TV network and broadcasting company (Korean Broadcasting System) in South Korea, where I analyzed transaction data from its video streaming service platform. That experience made me want to better understand why consumers behave the way they do, beyond simply observing what they purchase or watch. Marketing research is particularly interesting to me because I am also a consumer participating in the marketplace every day. Many research questions can come from behaviors and decisions that we encounter in our own lives, which makes the research feel very tangible and relevant.    

As a junior faculty member, publishing research in a leading journal is certainly rewarding. I do not see publication itself as the ultimate objective of research, but it gives me a sense that my work can contribute, even in a small way, to the cutting edge of human beings' collective knowledge. I find that very meaningful. 

What is your favorite part about being a Jayhawk?  

My favorite part about being a Jayhawk is the strong sense of community. I really appreciate how much pride people take in being part of KU while also being welcoming and supportive of one another. Whether I am interacting with students, faculty, staff or alumni, there is a shared sense of connection to the university. I especially enjoy being part of an environment where people are genuinely invested in students' growth and success. 

What would you see yourself doing if you weren’t a professor?  

Since I worked in industry before becoming a professor, I would probably still be working as an engineer or data analyst if I had not pursued an academic career. 

However, if I could go back to my teenage years and knew that academia was not an option, I think I would seriously consider working in the movie industry. I actually had an opportunity to participate in a movie production as a staff member, and I found the experience fascinating. So perhaps I would have pursued a career somewhere at the intersection of technology, data and filmmaking. 

What advice would you give your college self?  

I would tell my college self to expose myself to as many different courses, experiences, people, internships and opportunities as possible. As I have gotten older, I have become increasingly convinced that almost every experience has value, even when it does not seem useful at the time. Those experiences gradually shape your personality, perspectives, and skill set, and sometimes they become useful in ways you could never have anticipated. My college self might have found this advice a little boring, but I would still tell him very firmly: do not evaluate every experience only by its immediate payoff. Give yourself opportunities to explore. 

If you could require students to read one thing before graduation (outside of your class reading), what would it be and why? 

My first thought was to recommend a classic work of literature, but I would choose the paper “Attention Is All You Need.” It is the 2017 paper that introduced the Transformer architecture, which became foundational to modern large language models and many of today's generative AI systems and AI agents. I would recommend it for two reasons. 

First, the technology that grew out of this paper is creating enormous changes across industries. What I also find inspiring is that one of the co-authors, Aidan Gomez, was only about 20 years old when he worked on the paper — roughly the age of many college students. I think that is a powerful reminder that students do not necessarily have to wait until much later in their careers to contribute something important. 

Second, the world is changing in ways that would have been difficult to imagine even a few years ago. Students do not all need to become AI engineers, but I think it is valuable to understand at least some of the basic principles and ideas behind the technologies that are increasingly shaping their careers and everyday lives.