Kahyun Jeon

  • Assistant Professor

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Education

Ph.D. Architectural Engineering, Yonsei University, 2024

M.S. Architectural Engineering, Yonsei University, 2019

B. Arch. Architecture, Yonsei University, 2013
 

Research Interests

"Human Knowledge-infused AI-empowered Quality Management for Resilient Infrastructure and Communities." 
Kahyun Jeon's research interests lies in the development of AI-based construction management technology for a sustainable and resilient construction environment.  Her research has evolved from data-driven defect management to intelligent infrastructure production, operation, and maintenance that is resilient to potential risks such as aging defects and extreme climate change. As we already know, due to emerging climate changes or natural disasters, various types of defects will rapidly increase not only in our houses but also in social infrastructure. Nonetheless, most quality controls and operations in construction and infrastructure projects have relied heavily on experts鈥 experiences. 
Jeon's research group will seek the symbiotic knowledge transformation between humans and AI to preserve domain experts' tacit knowledge and advance AI for sustainable and resilient buildings and infrastructure management.  
The major research methodologies focus on construction automation centered on construction information and knowledge management, utilizing Natural Language Processing (NLP), Large Language Modeling (LLM), Agentic AI, Knowledge Graphs, and Human-Computer Interaction (HCI). 
 

Professional Affiliations & Memberships

Society Membership: American Society of Civil Engineers (ASCE)

Publications

A complete list of publications is available through .

Representative Paper List

  1. Jeon, K., and G. Lee. 2025. Hybrid large language model approach for prompt and sensitive defect management: A comparative analysis of hybrid, non-hybrid, and GraphRAG approaches. Advanced Engineering Informatics, 64: 103076.
  2. Jeon, K., G. Lee, S. Yang, Y. Kim, and S. Suh. 2023. 鈥淒ynamic building defect categorization through enhanced unsupervised text classification with domain-specific corpus embedding methods.鈥 Automation in Construction, 157: 105182.
  3. Jeon, K., G. Lee, S. Yang, and H. D. Jeong. 2022. 鈥淣amed entity recognition of building construction defect information from text with linguistic noise.鈥 Automation in Construction, 143: 104543.
  4. Jeon, K., G. Lee, S. Kang, H. Roh, J. Jung, K. Lee, and M. Baldwin. 2021. A relational framework for smart information delivery manual (IDM) specifications.鈥 Advanced Engineering Informatics, 49: 101319.
  5. Yong, G., Jeon, K., Gil, D., and Lee. G., (2023), Prompt Engineering for Zero-Shot and Few-Shot Defect Detection and Classification Using a Visual-Language Pretrained Model, Computer-Aided Civil and Infrastructure Engineering (CACIE) 38(11) 1536-1554
  6. Son, S., Lee, G., Jung, J., Kim, J., and Jeon, K., (2022), Automated generation of a model view definition from an information delivery manual using idmXSD and buildingSMART data dictionary. Advanced Engineering Informatics 54: 101731.

Expertise

Intelligent Construction Management, Building Information Modeling, Resilient and Sustainable Infrastructure Management, Construction Automation, Information and Knowledge Modeling, Large Language Model, Knowledge Graph, Human-AI Collaboration