Nhan Le (2026)

Qualifications

• PhD in Civil Engineering, The University of Melbourne, Australia (2026 – Present)
• MEng (Structural Engineering), Chulalongkorn University, Thailand (2024 – 2026)
• BEng (Civil Engineering), Hanoi University of Civil Engineering, Vietnam (2018 – 2023)

Prizes and Awards

• Melbourne Research Scholarships, University of Melbourne (2026)
• ASEAN/ NON-ASEAN scholarship program, Chulalongkorn University (2024)

Research Interests

• Machine Learning
• Composite Structures
• Structural optimisation

Employment

• None

Publications

1.    Le, D. N., Vu, Q. V., Pham, T. H., Huynh, V. T., & Tangaramvong, S. (2025). CurveSPG: An efficient framework for generating structural curves of the unstiffened steel plate girder under patch loading based on modified denoise diffusion model. Thin-Walled Structures, 113739. https://doi.org/10.1016/j.tws.2025.113739.

2.       Le, D. N., Pham, T. H., Pham, T. D., Kong, Z., Papazafeiropoulos, G., & Vu, Q. V. (2024). An efficient long short-term memory-based model for prediction of the load-displacement curve of concrete-filled double-skin steel tubular columns. Construction and Building Materials, 449, 138122. https://doi.org/10.1016/j.conbuildmat.2024.138122.

3.       Le, D. N., Pham, T. H., Papazafeiropoulos, G., Kong, Z., Tran, V. L., & Vu, Q. V. (2024). Hybrid machine learning with Bayesian optimization methods for prediction of patch load resistance of unstiffened plate girders. Probabilistic Engineering Mechanics, 76, 103624.  https://doi.org/10.1016/j.probengmech.2024.103624.

4.       D.-N. Le, Q.-V. Vu, and S. Tangaramvong, “An efficient deep learning approach for predicting the ultimate load and maximum lateral web deformation of unstiffened steel plate girders under patch loading” in Proceeding of The 30th National Convention on Civil Engineering, vol. 30, 2025.

5.       Vu, Q. V., Le, D. N., Pham, T. D., Gao, W., & Tangaramvong, S. (2025). An efficient procedure for prediction of the load-displacement curve of CFDST columns. Journal of Constructional Steel Research, 224, 109113. https://doi.org/10.1016/j.jcsr.2024.109113.

6.       Kong, Z., Le, D. N., Pham, T. H., Poologanathan, K., Papazafeiropoulos, G., & Vu, Q. V. (2024). Hybrid machine learning with optimization algorithm and resampling methods for patch load resistance prediction of unstiffened and stiffened plate girders. Expert Systems with Applications, 249, 123806. https://doi.org/10.1016/j.eswa.2024.123806.

7.       Vu, Q. V., Le, D. N., Pham, T. H., Gao, W., & Tangaramvong, S. (2026). Nonlinear optimization-based design of concrete-filled double-skin steel tubular columns under axial compression. Structures (Vol. 84, p. 110986).  https://doi.org/10.1016/j.istruc.2025.110986.

8.       Vu, Q. V., Kong, Le, D. N., Z., Papazafeiropoulos, G., & Pham, V. N. (2024). Hybrid machine learning with HHO method for estimating ultimate shear strength of both rectangular and circular RC columns. Steel and Composite Structures, 52(2), 145-163. 10.12989/scs.2024.52.2.145.

9.       Vu, Q. V., Le, D. N., Pham, T. H., Gao, W., & Tangaramvong, S. (2024). Hybrid machine learning with moth-flame optimization methods for strength prediction of CFDST columns under compression. Steel and Composite Structures, 51(6), 679-695. 10.12989/scs.2024.51.6.679.

10.     Thai, D. K., Le, D. N., Doan, Q. H., Pham, T. H., & Nguyen, D. N. (2024). A hybrid model for classifying the impact damage modes of fiber reinforced concrete panels based on XGBoost and Horse Herd Optimization algorithm. Structures (Vol. 60, p. 105872). https://doi.org/10.1016/j.istruc.2024.105872.

11.     Thai, D. K., Le, D. N., Doan, Q. H., Pham, T. H., & Nguyen, D. N. (2023). Classification models for impact damage of fiber reinforced concrete panels using Tree-based learning algorithms. Structures (Vol. 53, pp. 119-131).  https://doi.org/10.1016/j.istruc.2023.04.062.

12.     Pham, T. H., Le, D. N., Pham, V. T., Kong, Z., & Vu, Q. V. (2026). Efficient data-driven models for prediction of ultimate shear strength of reinforced concrete columns. Steel and Composite Structures, 58(1), 119.  https://doi.org/10.12989/scs.2026.58.1.119.

13.     Pham, T. H., Le, D. N., Pham, T. T., Nguyen, N. P., & Thai, D. K. (2026). A comprehensive framework for designing lightweight FRC panels under impact using machine learning and multi-objective optimization. STRUCTURAL ENGINEERING AND MECHANICS, 98(1), 117-146.

14.     Vu, Q. V., Le, D. N., Dinh, N. P., Papazafeiropoulos, G., & Tangaramvong, S. (2026). LamiNetDef: A novel physics-informed U-Net++ framework for predicting deflection shapes of laminated composite plates. Thin-Walled Structures, 228, 115041. https://doi.org/10.1016/J.TWS.2026.115041.