PeopleofSuperintelligence

Researcher

Kyoung-Kuk Kim

Also known as Kyoungkuk Kim

Kyoung-Kuk Kim is a financial engineer at KAIST whose work on risk analytics and simulation extends to machine learning for markets and insurance. After a mathematics degree from Seoul National University, a master's from Stanford and a business PhD from Columbia in 2008, he worked in quantitative credit at Lehman Brothers and Barclays Capital in New York. He joined KAIST's Department of Industrial and Systems Engineering in 2009 and was a Marsden postdoctoral fellow at the Fields Institute in 2010. His 2019 Quantitative Finance paper trained neural networks on Korea Exchange order book data, and a 2022 paper applied collaborative filtering to life insurance recommendations. He is a professor in the KAIST College of Business and an adjunct professor in KAIST's AX department, where reinforcement learning and control are among his core AI competencies.

Now at
KAIST
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Timeline

  1. 1999–2008

    Mathematics degrees and a Columbia PhD

    He earns a B.S. in mathematics from Seoul National University in 1999, graduating summa cum laude, and an M.S. in mathematics from Stanford in 2004. In 2008, he completes a Ph.D. in business at Columbia University.

  2. 2008–2009

    Quantitative credit in New York

    In 2008, he does quantitative credit research at Lehman Brothers in New York; from 2008 to 2009, he works in credit quantitative analytics at Barclays Capital in New York.

  3. 2009–2021

    Industrial engineering at KAIST

    He joins KAIST's Department of Industrial and Systems Engineering as an assistant professor in 2009 and becomes an associate professor in 2013. In 2021, he moves to KAIST's School of Management Engineering.

  4. 2010

    A Marsden fellowship at Fields

    He serves as a Jerrold E. Marsden Postdoctoral Fellow at the Fields Institute in 2010, during its thematic program on Quantitative Finance: Foundations and Applications.

  5. 2019

    Neural networks on order books

    With Geonhwan Ju and Dong-Young Lim, he publishes Learning multi-market microstructure from order book data in Quantitative Finance in 2019. The paper trains neural networks on order book data for 110 asset pairs, covering 97% of spot-futures pairs on the Korea Exchange, and shows that the models learn market features such as order imbalance, spread-volatility correlation and mean reversion.

  6. 2022

    A life insurance recommender

    In 2022, he coauthors a paper in Intelligent Systems in Accounting, Finance and Management on a personalized recommender system for life insurance products, with Hyeongwoo Kong, Wonje Yun, Weonyoung Joo, Ju-Hyun Kim, Il-Chul Moon and Woo Chang Kim. Using real customer data from South Korea, the study shows that collaborative filtering models apply to the insurance industry, especially when customer purchase information is added.

  7. As of October 2026

    KAIST professor and AX adjunct

    He is a professor in the KAIST College of Business and an adjunct professor in KAIST's AX department, where his research area is financial AI and risk analytics and his core AI competencies include simulation and digital twins, optimization and decision intelligence, and reinforcement learning and control. He heads the Digital Finance MBA program from 2022 to 2026 and, since 2024, is an associate editor of Operations Research.

Career

  1. Since 2009KAISTAssistant Professor, then Associate Professor, Head of Digital Finance MBA Program
  2. 2010University of TorontoJerrold E. Marsden Postdoctoral Fellow
  3. 2008Lehman Brothers
  4. 2008–2009Barclays Capital

Education

  1. 2008Columbia UniversityPh.D. in business
  2. 2004Stanford UniversityM.S. in mathematics
  3. 1999Seoul National UniversityB.S. in mathematics

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 named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Kyoung-Kuk Kim yet. Send us a free-licensed photo.

  1. KAIST College of Business Faculty Directory (Seoul): Kim Kyoung-Kuk business.kaist.edu. Checked 21 October 2026.
  2. Risk Lab: Kyoung-Kuk Kim, Professor, College of Business, KAIST sites.google.com. Checked 21 October 2026.
  3. Jerrold E. Marsden Postdoctoral Fellows - Fields Institute fields.utoronto.ca. Checked 21 October 2026.
  4. Learning multi-market microstructure from order book data - IDEAS/RePEc ideas.repec.org. Checked 21 October 2026.
  5. Constructing a personalized recommender system for life insurance products with machine-learning techniques - IDEAS/RePEc ideas.repec.org. Checked 21 October 2026.
  6. Faculty | AX, KAIST aicollege.kaist.ac.kr. Checked 21 October 2026.