Minki Kim
Also known as 김민기
Minki Kim is a KAIST marketing professor whose research connects AI with tutoring and health screening. He earned economics degrees at Seoul National University and the University of Chicago, joined KAIST College of Business in 2011, and published research on new-drug diffusion in 2012. A 2022 field experiment tested AI-assisted home tutoring, and a 2025 deep-learning study screened for Parkinson’s disease. He received KAIST research and teaching awards and was a member of the National AI Committee at a June 2025 forum. As of October 2026, he is a marketing professor at KAIST College of Business, heads KAIST Graduate School of Business, and chairs the KAIST MBA Program.
- Now at
- KAIST
Timeline
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2011
Economics and KAIST faculty
He earns a B.A. in economics from Seoul National University and M.A. and Ph.D. degrees in economics from the University of Chicago. He joins KAIST College of Business in 2011.
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2012
New-drug diffusion research
In 2012, he coauthors “New Drug Diffusion when Forward-Looking Physicians Learn from Patient Feedback and Detailing” with Ron Goettler and Pradeep Chintagunta for the Journal of Marketing Research.
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2022
AI-assisted home tutoring
In 2022, he coauthors a randomized field experiment on AI-assisted home tutoring. The trial finds that AI-generated diagnoses help tutors adapt to students’ learning needs and improve academic performance.
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2022–2023
KAIST research and teaching awards
He receives KAIST College of Business’s Impact Research Award in 2022 and Award for Excellence in Education in 2023. In 2023, KAIST gives him its Award for Academic Excellence in Commemoration of the 52nd Anniversary of Founding.
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Since 2023
KAIST business school leadership
Since 2023, he heads KAIST Graduate School of Business, chairs the KAIST MBA, and directs KAIST Seoul Business Incubation Center for Startups.
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2025
Deep learning for Parkinson’s screening
With Youngwook Koo and Woong Woo Lee, he coauthors “Predicting Parkinson’s Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data” in 2025. For the earlier prodromal period, adding all medication codes raises prediction accuracy to 0.922.
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June 2025
National AI Committee membership
At Financial News’s Future ICT Forum in June 2025, he speaks as a professor, head of KAIST Graduate School of Business, and member of the National AI Committee. He researches AI-driven business innovation and future convergence industries.
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As of October 2026
KAIST marketing professor
As of October 2026, he is a marketing professor at KAIST College of Business, heads KAIST Graduate School of Business, and chairs the KAIST MBA Program.
Career
- Since 2011KAISTProfessor, Head
- 2025National AI CommitteeMember
Education
Sources and credits
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- The 16th Future ICT Forum
- New drug diffusion when forward-looking physicians learn from patient feedback and detailing - Korea Advanced Institute of Science and Technology
- Home-tutoring services assisted with technology: investigating the role of artificial intelligence using a randomized field experiment
- Minki Kim - Korea Advanced Institute of Science and Technology
- Predicting Parkinson’s Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data
- People