SANG MIN LEE

Ph.D. [2023.03.-2027.02.(expected)]

• Interdisciplinary Program in Artificial Intelligence, Seoul National University
• Field of Study: AI for Resilient Infrastructure
• Advisor: Prof. Thomas H.-K. Kang

M.S. [2021.03.-2023.02.]

• Department of Architecture and Architectural Engineering, Seoul National University
• Field of Study: Structural Engineering
• Advisor: Prof. Thomas H.-K. Kang
• Thesis: Machine Learning Application to Automated Impact-Echo Test for Concrete Structures

B.S. [2016.03.-2021.02.]

• Department of Architecture and Architectural Engineering, Seoul National University
• Double Major in Department of Electrical and Computer Engineering, Seoul National University

High School Diploma [2013.03.-2016.02.]

• Korea Science Academy of KAIST
• Science High School for the Gifted

Visiting Researcher [Oct 2025 - Nov 2025]

• National Weather Center, University of Oklahoma, Norman, OK, USA
• Hydrometeorology and Remote Sensing Lab (Prof. Yang Hong)
• Collaborated on research activities about machine learning application to remote sensing and wind engineering

Machine Learning Engineer (Intern) [Sep 2024 - Feb 2025]

• Gentoo, Waddle Corporation, Seoul, Korea
• Developed LLM-as-a-Judge system including user simulator and LLM evaluator
• Alignment of LLM evaluator with human evaluation

Research Engineer (Intern) [Jul 2018 - Aug 2018]

• Chungyeon Architects (친환경계획그룹 청연건축사사무소), Seoul, Korea
• Data analysis of building energy performance evaluation
• ECO2, AutoCAD, and Python

• Machine Learning
• Wind Engineering
• Concrete
• Structural Health Monitoring
• Non-Destructive Testing

Journal Articles

1. Lee, S. M., Hong, J., Choi, H., & Kang, T. H.-K. (2025). Machine learning assisted method for automated impact-echo testing of concrete structures. Journal of Nondestructive Evaluation, 44(4), 121. paper →

2. Lee, S. M., Choi, H. S., Kim, C., & Kang, T. H.-K. (2025). Lightweight alternative machine learning model for automating concrete crack image classification. ACI Structural Journal, 122(5). paper →

3. Lee, Y. I., Lee, S. M., & Kang, T. H.-K. (2025). Multiclass deep support vector data description for structural health monitoring. Journal of Structural Engineering, 151(12). paper →

4. Ahn, B., Lee, D., Lee, S. M., & Kang, T. H.-K. (2023). 인공신경망을 활용한 위성사진 기반 기대풍속 예측 방법론에 관한 연구. 한국풍공학회논문집, 27(4), 135-142.

5. Lee, S. M., Choi, H., & Kang, T. H.-K. (2023). 스마트 임팩트 에코 검사를 위한 기계학습 응용. 건축(대한건축학회지), 67(3), 47-50.

6. Lee, S. M., Sung, H. S., & Kang, T. H.-K. (2022). Comparison of performance for predicting compressive strength of concrete using machine learning. Journal of the Korea Concrete Institute, 34(5), 505-513.

Conference Proceedings

1. Lee, S. M., & Kang, T. H.-K. (2026). 축소된 풍압공 계측자료를 활용한 딥러닝 기반 풍하중 시간이력 재구성. 한국풍공학회 제29회 학술대회, 29(1).

2. Lee, S. M., & Kang, T. H.-K. (2026). 콘크리트 내부결함 탐사를 위한 엣지AI 임팩트에코 시스템 개발 연구. 한국콘크리트학회 학술대회 논문집, 38(1), 267-268.

3. Park, H. G., Lee, S. M., & Kang, T. H.-K. (2026). 원전 격납건물 라이너플레이트 배면 콘크리트 내부 결함 모사를 통한 임팩트 에코 검사 적용 연구. 한국콘크리트학회 학술대회 논문집, 38(1), 273-274.

4. Lee, S. M., & Kang, T. H.-K. (2025). Retrieval augmented generation for assistance of using wind load design codes. The 10th Asia-Pacific Conference on Wind Engineering (APCWE10).

5. Lee, S. M., & Kang, T. H.-K. (2025). 딥러닝을 활용한 콘크리트 건물의 벽면 풍압계수 클러스터링 연구. 한국콘크리트학회 학술대회 논문집, 37(1), 13-14.

6. Lee, Y. I., Lee, S. M., & Kang, T. H.-K. (2024). 멀티클래스 심층 SVDD를 활용한 콘크리트 건축물 모니터링 연구. 한국콘크리트학회 학술대회 논문집, 36(2), 345-346.

7. Lee, S. M., & Kang, T. H.-K. (2024). 전문가 혼합 아키텍처를 활용한 건축구조기준 특화 대규모 언어모델 프레임워크. 한국콘크리트학회 학술대회 논문집, 36(2), 343-344.

8. Lee, S. M., Lee, Y. I., & Kang, T. H.-K. (2024). Multi-sphere deep SVDD for system identification of building structure. The 2024 World Congress on Advances in Civil, Environmental, and Materials Research (ACEM24).

9. Lee, S. M., Choi, H. S., Kim, C., & Kang, T. H.-K. (2024). Representation learning for classification of concrete crack images. The 2024 Structures Congress. Seoul, Korea.

10. Lee, S. M., Choi, H. S., Kim, C., & Kang, T. H.-K. (2024). Lightweighting concrete crack image classification machine learning models for on-device AI. 한국콘크리트학회 학술대회 논문집, 36(1), 57-58.

11. Lee, S. M., Choi, H., & Kang, T. H.-K. (2023). 머신러닝 응용 임팩트 에코 검사 자동화 연구. 한국콘크리트학회 학술대회 논문집, 35(1), 187-188.

12. Lee, S. M., & Kang, T. H.-K. (2022). Clustering wind pressure tap using dynamic time warping. 8th European-African Conference on Wind Engineering (EACWE2022). Bucharest, Romania.

13. Lee, S. M., & Kang, T. H.-K. (2022). Shear strength prediction of prestressed concrete based on machine learning. The 2022 Structures Congress. Seoul, Korea.

14. Lee, S. M., Sung, H. S., & Kang, T. H.-K. (2022). 머신러닝 기반 콘크리트 압축강도 예측 연구. 한국콘크리트학회 학술대회 논문집, 34(1), 179-180.

15. Lee, S. M., & Kang, T. H.-K. (2021). Prediction of wind pressure coefficients on high-rise building façade using LSTM RNN model for sensor reduction. The 2021 World Congress on Advances in Structural Engineering and Mechanics (ASEM21).

16. Lee, S. M., & Kang, T. H.-K. (2021). 장단기기억 순환신경망 기반 콘크리트 건물 벽면 풍압계수 예측 연구. 한국콘크리트학회 학술대회 논문집, 33(2), 155-156.

17. Lee, S. M., & Kang, T. H.-K. (2021). LSTM 네트워크를 활용한 콘크리트 건물의 벽면 풍압계수 예측 연구. 한국콘크리트학회 학술대회 논문집, 33(1), 189-190.

Theses

1. Lee, S. M. (2023). Machine learning application to automated impact-echo test for concrete structures [Master's thesis]. Seoul National University.

2. Lee, S. M. (2021). 조도에 따른 자동 개폐성 차양장치의 설계 및 사물인터넷 기술을 이용한 동작 최적화 알고리즘의 구현에 대한 연구 [Bachelor's thesis]. Seoul National University.

3. Lee, S. M. (2021). 마이크로그리드 내 에너지저장장치(ESS) 최적 운영 방안에 대한 연구 [Bachelor's thesis]. Seoul National University.

Early Publications

1. Lee, S. M., & Jeon, Y. C. (2016). GeoGebra를 활용한 Cycloid 곡선의 응용과 일반화에 대한 연구 [Graduation research]. Korea Science Academy of KAIST.

2. Lee, S. M., & Jeon, Y. C. (2015). A research on generalization and applications of cycloid. Geogebra Global Gathering 2015. Linz, Austria.

3. Jeon, Y. C., Cha, S. H., Lee, S. M., & Jung, S. H. (2015). Boolean 환과 그 일반화에 대한 연구. 한국수학교육학회 뉴스레터, 31(4), 11.

4. Lee, S. M., Lee, C. H., Jung, S. H., Jung, J. S., Kim, Y. G., Jeon, Y. C., & Cheon, J. A. (2014). 곱셈에 대한 교환법칙이 성립하지 않는 대수적 구조에 대한 연구 [R&E Report]. Korea Science Academy of KAIST.

5. Jeon, Y. C., Kim, Y. G., Lee, S. M., Lee, C. H., Jung, S. H., & Jung, J. S. (2014). 정역의 일반화에 대한 연구. 한국수학교육학회 뉴스레터, 30(5), 17.

• Hyper-converged Forensic Research Center for Infrastructure (2021-2027) - NRF Korea, funded by MSIT
• Smart City Innovative Technology Demonstration (2024-2025) - KAIA, funded by MOLIT
• Outstanding Patent Prototype Development (2023) - Seoul National University
• AI for Construction Research (2024) - Sejong Construction & SNU

• Lee, S. M., & Kang, T. H.-K. (2023). AI-based defect detection system inside concrete members. KR Patent 1,026,114,570,000.

• Lee, S. M., & Kang, T. H.-K. (2022). Wind load estimation system based on artificial intelligence. KR Patent 1,024,803,820,000.

• SNU AI Fellowship - 2025, 2026
• SNU AI Paper Competition Excellence Award - 2025
• SNU AI Graduate School Scholarship - 2023, 2024
• SNU Outstanding Teaching Assistant Award - 2022
• Korea Concrete Institute Outstanding Presentation Award - 2022
• Big Data Analysis Engineer (빅데이터분석기사) - 2025

Memberships

• ASCE (American Society of Civil Engineers)
• ACI (American Concrete Institute)
• KCI (Korea Concrete Institute)
• AIK (Architectural Institute of Korea)
• WEIK (Wind Engineering Institute of Korea)
• KSMI (Korea Institute for Structural Maintenance and Inspection)

Conference Organization

• WEIK Annual Conference (2025) - Organizing Committee, Seoul National University