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Jaehong Lee

Professor

Sejong University

South Korea

Research Interests

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Professors in South Korea Professors in Structural Engineering Structural Engineering professors in South Korea

About

Jaehong Lee is a Professor at Sejong University in South Korea. His research areas include design optimization, tensegrity structures, and the load-bearing capabilities of ultra-thin shells. His recent publications focus on advancements in surrogate modeling and neural networks. He is dedicated to furthering knowledge in structural engineering and materials science.

Articles (17)

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2026

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2026

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2026

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2023

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2022

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2022

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2022

Collaborators (5)

Jin-Kook Kim

Seoul National University

SOUTH KOREA

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Chenxi Peng

University of Melbourne

AUSTRALIA

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Thuc Vo

Associate Professor in Structural Engineering

La Trobe University

AUSTRALIA

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Phuong Tran

Senior Lecturer

RMIT University

AUSTRALIA

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Viet-Linh Tran

Lecturer

Van Lang University

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Jaehong Lee

Research Interests

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About

Articles (17)

Drawing-to-moment: A machine learning approach to early-stage structural evaluation

Physics-informed Fourier neural operator for the bending analysis of bi-directional functionally graded beams with variable cross-sections

Shooting neural network for multipoint boundary value problems

Prediction and reliability analysis of ultimate axial strength for outer circular CFRP-strengthened CFST columns with CTGAN and hybrid MFO-ET model

3D material optimization of functionally graded shells using incremental Kriging surrogates and adaptive infill strategies

A Neural Network Approach for Domain Reduction in High-Dimensional Optimization Problem

A novel scalable graph neural network for response prediction of structures with different topologies

An efficient NURBS-based reconstruction approach to isogeometric analysis of triply periodic minimal surface structures

Enhancing the prediction accuracy of real-world seismic data using various Decision tree-based models

Optimal non-guideline blended composite laminate design using generative stacking sequence and optimal thickness prediction models

Physics-Informed Neural Network with Normalization and Full-Imposed Boundary Conditions for Solving Inverse Problems

Physics-informed Fourier neural operator: A neural operator framework for non-prismatic beam bending analysis

Simultaneous imposition of initial and boundary conditions via decoupled physics-informed neural networks for solving initial-boundary value problems

Performance of meta concrete panels subjected to explosive load: Numerical investigations

Deep Neural Networks for Form-Finding of Tensegrity Structures

An Improved Blind Kriging Surrogate Model for Design Optimization Problems

Load-Carrying Capacity of Ultra-Thin Shells with and without CNTs Reinforcement

Collaborators (5)

Jin-Kook Kim

Chenxi Peng

Thuc Vo

Phuong Tran

Viet-Linh Tran

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