The Manufacturing AI Research Center was newly established on January 1, 2024, as a direct organization under the Vice President of the Korea Institute of Industrial Technology. It aims to concentrate capabilities on developing an AI platform for the "AI-based innovation in manufacturing" initiative, promoting the rapid dissemination of the developed platform, and fostering in-house AI experts.
Hong-In Won, Ph.D.
Principal Researcher · Korea Institute of Industrial Technology
Researcher Profile
Hong-In Won, Ph.D.
Principal Researcher, Korea Institute of Industrial Technology (KITECH)
Head of the Manufacturing AI Cooperation Team
Dr. Hong-In Won is a Principal Researcher at KITECH. Since 2019, he has served as a KITECH research principal investigator, working across manufacturing AI, digital transformation, and data-driven production systems. He received his Ph.D. in Mechanical Design Engineering from Hanyang University and previously worked as a postdoctoral researcher at TU Dresden.
Research Focus
Manufacturing AI
AI methods and implementation strategies for practical manufacturing innovation and industrial digital transformation.
Digital Twin Systems
Data, simulation, and virtual validation approaches for intelligent production systems.
Data-Driven Production
Process intelligence, quality-oriented analytics, and collaborative deployment of AI in production environments.
Selected Research Outputs and Engagement
Selected External Engagements
- Unite Seoul 2026 — industry presentation, “A Unity Digital Twin-based Synthetic Data Pipeline for Manufacturing AI.”
- KOREATECH Future Technology Education Center Faculty Training (2026) — “Building and Applying Multi-Agent Systems in the AI Agent Era.”
- Korea Institute of Civil Engineering and Building Technology (2026) — invited workshop, “The Evolution of AI Agent Engineering.”
Professional Leadership & Service
- Joint Faculty Member, Hanyang University Graduate School (2026–2027).
- Executive Director and Academic Committee Member, Korean Society for Noise and Vibration Engineering.
- Expert Committee Member for equipment-diagnosis qualification and training evaluation.
Selected Research Outputs
- “Adaptive Task Token Framework for Multi-Agent Logistics Operations.” IEEE Robotics and Automation Letters, 2026. Accepted for publication.
- “Digital twin-based test-time adaptation for robust visual perception in manufacturing.” Engineering Applications of Artificial Intelligence, 2026.
- “AI-driven multivariate time series forecasting of transmembrane pressure in ultrafiltration: A stationarity-aware approach.” Journal of Water Process Engineering, 2025.
- “FALCON: Fine-grained Alignment for Counting Objects in Industry.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2026.
- “Digital Twin-based Robust Viewpoint Sampling for Automated Robotic Inspection.” IEEE International Conference on Industrial Cyber-Physical Systems, 2026.
Public Verification and Research Links
Official affiliation, publication record, and public research activity.