PeopleofSuperintelligence

Researcher

Hakjin Chung

Also known as Hakjin Jung

Hakjin Chung is an associate professor of operations strategy and management science at the KAIST College of Business whose research covers platform market design, pricing, algorithmic fairness and privacy-preserving AI. He earned a B.A. in economics at Seoul National University in 2006, an M.S. in statistics at Columbia University in 2010 and a Ph.D. in technology and operations at the University of Michigan's Ross School of Business in 2016, then joined KAIST as an assistant professor in September 2016. His papers include a rescaled choice-model approximation for assortment optimization in 2019, a study of selfish customers in service systems in 2020 and Dynamic Pricing with Point Redemption in 2022, and he received the KORMS Outstanding Research Award in 2023 and the KAIST Excellent Research Award in 2024. Since September 2024, he is a tenured professor, and the KAIST AI College faculty list gives reinforcement learning and control and multi-agent systems among his core AI competencies.

Now at
KAIST

Timeline

  1. 2006–2016

    Degrees at Seoul, Columbia, Michigan

    He earns a B.A. in economics from Seoul National University in 2006 and an M.S. in statistics from Columbia University in 2010. In 2016, he completes a Ph.D. in technology and operations at the Stephen M. Ross School of Business, University of Michigan.

  2. 2016–2022

    Assistant professor at KAIST

    He joins the KAIST College of Business as an assistant professor in September 2016. He becomes an associate professor there in September 2022.

  3. 2019

    Rescaled multi-attempt choice model

    With Hyun-Soo Ahn and Stefanus Jasin, he publishes a rescaled multi-attempt approximation of choice models and its application to assortment optimization in Production and Operations Management in 2019. The approximation covers any random-utility choice model and is exact for the multinomial logit.

  4. 2020

    Benefit of anarchy in queues

    In 2020, he publishes "The potentially negative effects of cooperation in service systems" in Advances in Applied Probability with Hyun-Soo Ahn and Rhonda Righter. The paper studies a game in which a server invests in capacity before customers decide whether to join, and shows that customers acting selfishly can reach a greater overall utility than customers coordinated to maximize it.

  5. 2022

    Dynamic pricing with reward points

    In 2022, he publishes "Dynamic Pricing with Point Redemption" in Manufacturing & Service Operations Management with Hyun-Soo Ahn and So Yeon Chun. The paper builds a choice model in which a consumer pays with cash or points, and shows that a seller can benefit from allowing reward sales even when the reimbursement rate is substantially lower than the cash price.

  6. 2023

    KORMS research award

    In 2023, he receives the KORMS Outstanding Research Award. He also coauthors a Sustainability article with Jiung Lee and Naeun Cho on how a firm's operational efficiency shapes its adoption of environmental management practices.

  7. 2024

    Subsidy policy and KAIST award

    In 2024, he coauthors "Optimal Subsidy Policy for Innovation: Technology Push and Demand Pull" in Production and Operations Management with Hyun-Soo Ahn, Myeonghun Lee and Sangwon Kim, which characterizes when supply-side or demand-side subsidies work better. He receives the KAIST Excellent Research Award in 2024.

  8. Since 2024

    Tenured professor at KAIST

    Since September 2024, he is an associate professor with tenure in operations strategy and management science at the KAIST College of Business, and he is a visiting associate professor at Aoyama Gakuin University in Tokyo in 2026. His research covers platform market design, pricing and contracts, algorithmic fairness and privacy-preserving AI, and the KAIST AI College faculty list gives him as an adjunct professor with core AI competencies in reinforcement learning and control and in multi-agent systems.

Career

  1. Since 2016KAISTAssistant Professor
  2. From 2026Aoyama Gakuin UniversityVisiting Associate Professor

Education

  1. 2016University of MichiganPh.D.
  2. 2010Columbia UniversityM.S.
  3. 2006Seoul National UniversityB.A.

From the biography.

  1. The United States employs an estimated 48% of people shaping AIIncludes KAIST. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes KAIST. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes KAIST. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. 44% of AI career moves go from one university to anotherIncludes KAIST. We estimate how 26,439 AI career moves link universities, companies, labs, nonprofits and government research centers, with decade counts, net flows and the top paths.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Hakjin Chung sites.google.com. Checked 21 October 2026.
  2. (Rescaled) Multi-Attempt Approximation of Choice Model and Its Application to Assortment Optimization ideas.repec.org. Checked 21 October 2026.
  3. The potentially negative effects of cooperation in service systems | Advances in Applied Probability | Cambridge Core doi.org. Checked 21 October 2026.
  4. Dynamic Pricing with Point Redemption ideas.repec.org. Checked 21 October 2026.
  5. Hakjin Chung - Research sites.google.com. Checked 21 October 2026.
  6. Faculty | AX aicollege.kaist.ac.kr. Checked 21 October 2026.