Ansan Research Institute ← Software
Profile

Seokki Cha, Ph.D.

Technology Policy & Computational Policy

Ansan Research Institute — applying computational methods to urban and regional policy, and building the software that puts the findings to work.

7Journal articles
5Patents filed
11Research reports
3Systems in service

Research

Policy questions are treated as computational problems — measured, modelled, and then built into something a city can actually operate.

The work sits between science & technology policy and applied computation. It covers AI governance and regulatory design, energy transition planning, data-driven diagnosis of local economies, and evaluation methods for public programmes — using machine learning, simulation, sensitivity analysis and econometric identification.

A second strand turns those findings into working systems. The three services published by the institute — a civic participation platform, an automated MRV reporting system, and a locally hosted conversational AI — all began as research outputs and are now open for anyone to use.

Education

  • Ph.D.

    Science & Technology Policy — Computational Policy

    Hanyang University, Interdisciplinary Program in Science & Technology Policy

  • M.S.

    Quantum & Nuclear Engineering

    Sejong University

  • B.S.

    Radiological Science & Engineering

    Yonsei University

Appointments

  • 2025 –

    Research Fellow — Director, Urban Transportation Research Division

    Ansan Research Institute

  • 2025 –

    Committee Member

    Sustainable Energy City Committee, Ansan City

  • 2022 – 2025

    Senior Researcher

    Policy & Strategy Division, Korea Institute of Science and Technology Information (KISTI)

  • 2022

    Research Specialist

    Research Planning Center, KAIST

  • 2016 – 2021

    Researcher

    National Radiation Emergency Medical Center, Korea Institute of Radiological & Medical Sciences (KIRAMS)

  • 2013 – 2016

    Researcher

    Radiation Safety Division, Korea Foundation of Nuclear Safety

Journal articles

SSCI

  1. Cha, S. (in press). Policy mix framework for AI regulation: A game-theoretic analysis of risk-based direct regulation and standardization approaches. Information Development.
  2. Cha, S. (2024). Towards an international regulatory framework for AI safety: Lessons from the IAEA's nuclear safety regulations. Humanities and Social Sciences Communications, 11(1), 1–13.

SCIE

  1. Cha, S. (2025). The potential role of small modular reactors (SMRs) in addressing the increasing power demand of the artificial intelligence industry: A scenario-based analysis. Nuclear Engineering and Technology, 57(4), 103314.
  2. Cha, S. (2024). Ordinary least squares regression-based difference-in-differences estimation approach for evaluating specialized nuclear emergency preparedness program. International Journal of Radiation Research, 22(2), 405–411.

KCI

  1. Cha, S. (2025). A multidimensional evaluation framework for SME innovation in the Fourth Industrial Revolution–ESG dual transition: A sensitivity analysis approach using Monte Carlo sampling and Sobol indices. 중소기업정책연구, 10(1), 45–84. in Korean
  2. Cha, S., Jeong, D., & Seo, B. (2024). Digital divide and social inclusion in an AI-based society: A foresight study. 지식경영연구 (Knowledge Management Research), 25(3), 173–200. in Korean
  3. Cha, S., & Park, K. (2024). Integrating machine learning with data envelopment analysis for enhanced R&D efficiency & optimizing resource allocation in the specialized field. Asian Journal of Innovation and Policy, 13(1), 1–28.

Patents

Filed 2026 · KIPO

  1. Hybrid RAG-based regulation guidance system and method thereof supporting anti-hallucination and recursive table data search. 10-2026-0053228
  2. Hybrid knowledge base construction system and method thereof based on metadata tagging specialized for public institution regulations. 10-2026-0053187
  3. System and method for tracking commercial district lifecycle using time-series weight decay function and 3-layer multidimensional framework. 10-2026-0053226
  4. System and method for automatic classification of commercial district types based on unsupervised learning with dynamic rendering options and customized policy recommendation. 10-2026-0053215
  5. System and method for calculating commercial district vitality reflecting spatial continuity using multi-threshold density clustering and hexagonal grid system. 10-2026-0053204

Research reports

Ansan Research Institute

  1. Cha, S., et al. (2026). Prioritizing AI adoption across Ansan's public services: Building and validating a multi-agent, locally hosted LLM prototype (PoC). in Korean
  2. Cha, S., et al. (2026). Data-driven classification and revitalization policy for Ansan's commercial districts: A machine-learning diagnostic and spatial-grid decision support system. in Korean
  3. Cha, S., et al. (2025). Baseline study for Ansan's Third Local Energy Plan. in Korean
  4. Cha, S., et al. (2025). Preliminary study on a distributed-energy special district based on fuel cell generation and clean hydrogen in Ansan. in Korean

KISTI

  1. Cha, S., et al. (2024). Advancing information analysis of science, technology and industry trends. ISBN 978-89-294-1753-6 · in Korean
  2. Cha, S., et al. (2024). KISTI's challenge: Data-driven approaches to national and social problems. ISBN 978-89-294-1539-6 · in Korean
  3. Choi, J., Cha, S., et al. (2023). Policy and strategy research on science and technology data. in Korean
  4. Choi, H., Cha, S., et al. (2022). Research programme planning support. in Korean

KIRAMS

  1. Cho, M., Cha, S., et al. (2021). Advancing operations for special disaster medical response. in Korean
  2. Cha, S., et al. (2020). Thyroid blocking agents: Case studies and international trends. ISBN 979-11-967235-4-5 · in Korean
  3. Cho, M., Cha, S., et al. (2020). Advancing operations of the National Radiation Emergency Medical Center. in Korean