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Research

Data-Driven Social Science Research Group

This research group explores the economics and management issues of innovation and entrepreneurship based on data-driven analysis approaches that include machine learning, natural language process, text mining, network analysis. By doing so, the group tries to identify the unique and valuable findings that has not been found with traditional approaches in social science.

Achievement
  • 01
    Artificial Intelligence Today 2021 / 글로벌 AI 혁신경쟁: 현재와 미래

    김원준, 김진우, 김하나, 김태균 / 2021 / KAIST CISP & Clarivate

  • 02
    Global Competition for Sustainable AI Chip Innovation Ecosystem / 글로벌 AI 반도체 혁신과 경쟁-현재와 미래

    김원준, 김진우, 김하나, 김태균 / 2023 / 

People
  • Prof. Alex Coad

    Waseda University Business School

  • Prof. Kyoung Ryul Park

    KAIST Graduate School of Science and Technology Policy

  • Prof. Hyejin Youn

    Northwestern University Kellogg School of Management

  • Prof. Kiho Kwak

    Pukyong National University Graduate School of Management of Technology

  • Prof. Jeff Furman

    Boston University Questrom School of Business

  • Prof. Hawoong Jeong

    KAIST Department of Physics

  • Prof. Scott Stern

    MIT Sloan School of Management

  • Prof. Ji Yong Eom

    KAIST School of Business and Technology Management

  • Prof. Minki Kim

    KAIST Department of Management Engineering

  • Prof. Insong Kim

    MIT Department of Political Science

  • Prof. Wonjoon Kim

    KAIST School of Business and Technology Management