Sang Min Lee

Ph.D. Candidate in Artificial Intelligence
Seoul National University

201612445@snu.ac.kr
concrete-sangminlee.github.io
Google Scholar
Sang Min Lee
ORCID
0000-0002-6822-5252
GitHub
github.com/concrete-sangminlee

Research Interests

Automated non-destructive testing; Structural health monitoring; Data-driven wind engineering; Language models for building codes; Machine learning for concrete properties

Education

  1. 2023–2027 (expected)

    Ph.D. in Artificial Intelligence

    Interdisciplinary Program in Artificial Intelligence, Seoul National University

    • Research: AI for resilient infrastructure and wind engineering
    • Advisor: Prof. Thomas H.-K. Kang
  2. 2021–2023

    M.S. in Structural Engineering

    Department of Architecture and Architectural Engineering, Seoul National University

    • Thesis: Machine Learning Application to Automated Impact-Echo Test for Concrete Structures
    • Advisor: Prof. Thomas H.-K. Kang
  3. 2016–2021

    B.S. in Architectural Engineering

    Department of Architecture and Architectural Engineering, Seoul National University

    • Double major: Electrical and Computer Engineering (2017–2021)
  4. 2013–2016

    Diploma

    Korea Science Academy of KAIST, science high school for gifted students

    • Senior Vice President, 24th Student Council; Deputy Head of International Affairs, 23rd Student Council
    • Exchange programs at Moscow Chemical Lyceum, Russia (2014) and G.T. (Ellen Yeung) College, Hong Kong (2015)

Research and Professional Experience

  1. Mar 2021 – present

    Graduate Research Assistant

    Hi-performance Structural Engineering Lab, Seoul National University

    • Advisor: Prof. Thomas H.-K. Kang
    • Machine learning for impact-echo testing, structural health monitoring, wind engineering, and building codes
  2. Oct–Nov 2025

    Visiting Researcher

    National Weather Center, University of Oklahoma, Norman, OK, USA

    • Hydrometeorology and Remote Sensing Lab, hosted by Prof. Yang Hong
    • Visiting student, School of Civil Engineering and Environmental Sciences, Gallogly College of Engineering
    • Collaborated on machine learning for remote sensing and wind engineering
  3. Dec 2018 – Feb 2021

    Undergraduate Research Assistant

    Seoul National University

    • Jan–Feb 2021, HpSE Lab: wind pressure coefficient prediction for wind-resistant building design
    • Oct 2019 – Feb 2020, SNUCEM: AHP analysis for improving military dining facilities
    • Dec 2018 – Feb 2019, AEPRL: designed and built an IoT device (hardware and software) that detects surface condensation indoors
  4. Jul–Aug 2018

    Research Engineer (Intern)

    Chungyeon Architects, Seoul, Korea

    • Data analysis for building energy performance evaluation with ECO2, AutoCAD, and Python

Publications6 journal articles · 20 conference papers

Journal Articles

  1. J6Lee, 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. SCIE doi:10.1007/s10921-025-01260-3
  2. J5Lee, 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). SCIE
  3. J4Lee, 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). SCIE doi:10.1061/JSENDH.STENG-14823
  4. J3Ahn, B., Lee, D., Lee, S. M., & Kang, T. H.-K. (2023). A methodology for predicting expected wind speed from satellite images using artificial neural networks (in Korean). Journal of the Wind Engineering Institute of Korea, 27(4), 135–142. KCI
  5. J2Lee, S. M., Choi, H., & Kang, T. H.-K. (2023). Machine learning applications for smart impact-echo testing (in Korean). Review of Architecture and Building Science (Architectural Institute of Korea), 67(3), 47–50.
  6. J1Lee, 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. KCI

Conference Papers

  1. C20Lee, S. M., & Kang, T. H.-K. (2026). CoMuRAG: Condition-mutated hard negatives for safety-sensitive Korean building-code retrieval. ACM/IEEE Joint Conference on Digital Libraries (JCDL 2026).
  2. C19Park, H. G., Lee, S. M., & Kang, T. H.-K. (2026). Experimental study on impact-echo response characteristics of defects behind liner plates in nuclear containment buildings (in Korean). Proceedings of the Korea Concrete Institute Conference, 38(2).
  3. C18Park, H. G., Lee, S. M., & Kang, T. H.-K. (2026). Modified impact-echo testing of liner-plate-backed concrete in nuclear containment buildings. ACEM26 / Structures26.
  4. C17Lee, S. M., & Kang, T. H.-K. (2026). Deep learning-based reconstruction of wind load time histories from reduced pressure tap measurements (in Korean). Proceedings of the 29th Annual Conference of the Wind Engineering Institute of Korea, 29(1), 73–74.
  5. C16Lee, S. M., & Kang, T. H.-K. (2026). Development of an edge-AI impact-echo system for detecting internal defects in concrete (in Korean). Proceedings of the Korea Concrete Institute Conference, 38(1), 267–268.
  6. C15Park, H. G., Lee, S. M., & Kang, T. H.-K. (2026). Applying impact-echo testing to simulated internal defects in concrete behind liner plates of nuclear containment buildings (in Korean). Proceedings of the Korea Concrete Institute Conference, 38(1), 273–274.
  7. C14Lee, 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).
  8. C13Lee, S. M., & Kang, T. H.-K. (2025). Clustering of façade wind pressure coefficients on concrete buildings using deep learning (in Korean). Proceedings of the Korea Concrete Institute Conference, 37(1), 13–14.
  9. C12Lee, Y. I., Lee, S. M., & Kang, T. H.-K. (2024). Monitoring of concrete buildings using multiclass deep SVDD (in Korean). Proceedings of the Korea Concrete Institute Conference, 36(2), 345–346.
  10. C11Lee, S. M., & Kang, T. H.-K. (2024). A large language model framework specialized for building structural design codes using a mixture-of-experts architecture (in Korean). Proceedings of the Korea Concrete Institute Conference, 36(2), 343–344.
  11. C10Lee, 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).
  12. C9Lee, 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.
  13. C8Lee, S. M., Choi, H. S., Kim, C., & Kang, T. H.-K. (2024). Lightweighting concrete crack image classification machine learning models for on-device AI. Proceedings of the Korea Concrete Institute Conference, 36(1), 57–58.
  14. C7Lee, S. M., Choi, H., & Kang, T. H.-K. (2023). Automating impact-echo testing with machine learning (in Korean). Proceedings of the Korea Concrete Institute Conference, 35(1), 187–188.
  15. C6Lee, 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.
  16. C5Lee, S. M., & Kang, T. H.-K. (2022). Shear strength prediction of prestressed concrete based on machine learning. The 2022 Structures Congress, Seoul, Korea.
  17. C4Lee, S. M., Sung, H. S., & Kang, T. H.-K. (2022). Machine learning-based prediction of concrete compressive strength (in Korean). Proceedings of the Korea Concrete Institute Conference, 34(1), 179–180.
  18. C3Lee, 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).
  19. C2Lee, S. M., & Kang, T. H.-K. (2021). Prediction of façade wind pressure coefficients on concrete buildings using long short-term memory recurrent neural networks (in Korean). Proceedings of the Korea Concrete Institute Conference, 33(2), 155–156.
  20. C1Lee, S. M., & Kang, T. H.-K. (2021). Prediction of façade wind pressure coefficients on concrete buildings using LSTM networks (in Korean). Proceedings of the Korea Concrete Institute Conference, 33(1), 189–190.

Theses

  1. T3Lee, S. M. (2023). Machine learning application to automated impact-echo test for concrete structures [Master's thesis]. Seoul National University.
  2. T2Lee, S. M. (2021). Design of an illuminance-responsive automatic shading device and an IoT-based motion optimization algorithm (in Korean) [Bachelor's thesis]. Department of Architecture and Architectural Engineering, Seoul National University.
  3. T1Lee, S. M. (2021). Optimal operation of energy storage systems (ESS) in microgrids (in Korean) [Bachelor's thesis]. Department of Electrical and Computer Engineering, Seoul National University.

Patents

  1. 2023

    AI-based defect detection system inside concrete members

    Lee, S. M., & Kang, T. H.-K. Korean Patent 10-2611457, registered

  2. 2022

    Wind load estimation system based on artificial intelligence

    Lee, S. M., & Kang, T. H.-K. Korean Patent 10-2480382, registered

Research Projects

  1. 2021–2027

    Hyper-converged Forensic Research Center for Infrastructure, NRF Korea, funded by MSIT

  2. 2024–2025

    Smart City Innovative Technology Demonstration Project, KAIA, funded by MOLIT

  3. 2024

    AI for Construction Research Project, SNU, funded by Sejong Construction

  4. 2023

    Outstanding Patent Prototype Development Project, Seoul National University

Teaching ExperienceTeaching assistant, Seoul National University

  1. 2022–2024

    Architecture and AI, Spring 2022, 2023, and 2024

    Taught hands-on sessions on deep neural networks

  2. 2021–2022

    Introduction to IoT, AI, and Big Data, Spring and Fall 2021 and 2022; head TA in Fall 2022

    Evaluated IoT projects and ran Arduino UNO labs

  3. 2021–2022

    IoT and Creative Engineering Design, Fall 2021 and Spring 2022

    Evaluated IoT projects; labs on Arduino UNO, Teensy, ESP32, and STM boards

  4. 2021–2022

    Creative Engineering Design, Fall 2021 and Spring 2022

    Evaluated IoT projects; labs on Arduino UNO and ESP32

  5. 2022

    Structural Experiment and Material, Spring 2022

    Euler buckling, truss deflection, and two-way shake-table seismic design experiments

  6. 2021

    Mechanics of Materials for Architectural Engineering, Fall 2021

    Problem sessions on structural engineering fundamentals

  7. 2021

    Prestressed Concrete, Fall 2021

    Course management, with a focus on post-tensioned structures

  8. 2021

    Computation in Architectural Engineering, Spring 2021

    MATLAB labs for structural engineering students

Honors and Awards

  1. 2025–2026

    SNU AI Fellowship, Interdisciplinary Program in Artificial Intelligence, SNU

    Four semesters, Spring 2025 to Fall 2026

  2. 2025

    Excellence Award, SNU AI Paper Competition, Interdisciplinary Program in Artificial Intelligence, SNU

    Included travel support to attend NeurIPS

  3. 2023–2024

    SNU AI Graduate School Scholarship, Interdisciplinary Program in Artificial Intelligence, SNU

    Four semesters, Spring 2023 to Fall 2024

  4. 2022

    Outstanding Teaching Assistant Award, College of Engineering, SNU

    Fall 2022

  5. 2022

    Outstanding Presentation Award, Korea Concrete Institute

    Spring Conference 2022

  6. 2021

    Sen Engineering Group Scholarship, Department of Architecture and Architectural Engineering, SNU

    Fall 2021

  7. 2019

    Gwanakhoe Foundation, Gwanakhoe, SNU

    Spring and Fall 2019

Certifications

  1. Jul 2025

    Big Data Analysis Engineer, Korea Data Agency

Professional Service

Reviewing

  1. 2024–present

    Wind and Structures, Reviewer

    SCIE journal in wind engineering

Conference Organization

  1. 2025

    28th WEIK Annual Conference, Organizing committee member

    Held at Seoul National University

Professional Memberships

  1. since 2021

    Korea Concrete Institute (KCI), regular member

  2. since 2021

    American Concrete Institute (ACI), student member

  3. since 2023

    Architectural Institute of Korea (AIK), regular member

  4. since 2023

    Korea Institute for Structural Maintenance and Inspection (KSMI), student member

  5. since 2023

    Wind Engineering Institute of Korea (WEIK), student member

  6. since 2025

    American Society of Civil Engineers (ASCE), student member

Outreach

  1. 2016–2018

    Edushare Korea, Mathematics teacher; lead teacher of the Uiwang Bugok center

    Taught mathematics to students from low-income families

Skills