| Deep generative design: Integration of topology optimization and generative models S Oh, Y Jung, S Kim, I Lee, N Kang Journal of Mechanical Design 141 (11), 111405, 2019 | 466 | 2019 |
| Modeling, analysis, and optimization under uncertainties: a review E Acar, G Bayrak, Y Jung, I Lee, P Ramu, SS Ravichandran Structural and Multidisciplinary Optimization 64 (5), 2909-2945, 2021 | 90 | 2021 |
| Confidence-based design optimization for a more conservative optimum under surrogate model uncertainty caused by Gaussian process Y Jung, K Kang, H Cho, I Lee Journal of Mechanical Design 143 (9), 091701, 2021 | 34 | 2021 |
| Reliability measure approach for confidence-based design optimization under insufficient input data Y Jung, H Cho, I Lee Structural and Multidisciplinary Optimization 60, 1967-1982, 2019 | 30 | 2019 |
| Statistical model calibration and design optimization under aleatory and epistemic uncertainty Y Jung, H Jo, J Choo, I Lee Reliability Engineering & System Safety 222, 108428, 2022 | 26 | 2022 |
| Optimal design of experiments for optimization-based model calibration using Fisher information matrix Y Jung, I Lee Reliability Engineering & System Safety 216, 107968, 2021 | 25 | 2021 |
| Intelligent initial point selection for MPP search in reliability-based design optimization Y Jung, H Cho, I Lee Structural and Multidisciplinary Optimization 62, 1809-1820, 2020 | 19 | 2020 |
| MPP-based approximated DRM (ADRM) using simplified bivariate approximation with linear regression Y Jung, H Cho, I Lee Structural and multidisciplinary optimization 59, 1761-1773, 2019 | 19 | 2019 |
| Reliability-based multi-scale design optimization of composite frames considering structural compliance and manufacturing constraints Z Duan, Y Jung, J Yan, I Lee Structural and Multidisciplinary Optimization 61, 2401-2421, 2020 | 18 | 2020 |
| Modified augmented Lagrangian coordination and alternating direction method of multipliers with parallelization in non-hierarchical analytical target cascading Y Jung, N Kang, I Lee Structural and Multidisciplinary Optimization 58, 555-573, 2018 | 14 | 2018 |
| A reanalysis-based multi-fidelity (RBMF) surrogate framework for efficient structural optimization M Lee, Y Jung, J Choi, I Lee Computers & Structures 273, 106895, 2022 | 13 | 2022 |
| Probabilistic analytical target cascading using kernel density estimation for accurate uncertainty propagation Y Jung, J Lee, M Lee, N Kang, I Lee Structural and Multidisciplinary Optimization 61, 2077-2095, 2020 | 13 | 2020 |
| Determination of sample size for input variables in RBDO through bi-objective confidence-based design optimization under input model uncertainty Y Jung, H Cho, Z Duan, I Lee Structural and Multidisciplinary Optimization 61, 253-266, 2020 | 10 | 2020 |
| Optimization-based model calibration of marginal and joint output distributions utilizing analytical gradients H Jo, K Lee, M Lee, Y Jung, I Lee Structural and Multidisciplinary Optimization 63, 2853-2868, 2021 | 9 | 2021 |
| An expected uncertainty reduction of reliability: adaptive sampling convergence criterion for Kriging-based reliability analysis M Kim, Y Jung, M Lee, I Lee Structural and Multidisciplinary Optimization 65 (7), 206, 2022 | 7 | 2022 |
| Distribution estimation of Johnson-Cook parameters considering correlation in quasi-static state J Choo, Y Jung, H Jo, J Kim, I Lee International Journal of Mechanical Sciences 244, 108086, 2023 | 6 | 2023 |
| An effective active learning strategy for reliability-based design optimization under multiple simulation models S Yang, M Lee, Y Jung, H Cho, W Hu, I Lee Structural Safety 107, 102426, 2024 | 2 | 2024 |
| A bayesian model calibration under insufficient data environment J Choo, Y Jung, I Lee Structural and Multidisciplinary Optimization 65 (3), 96, 2022 | 2 | 2022 |
| Auxetic kirigami structure-based self-powered strain sensor with customizable performance using machine learning J Gu, Y Jung, J Ahn, J Ahn, J Choi, B Kang, Y Jeong, JH Ha, T Kim, ... Nano Energy 130, 110124, 2024 | 1 | 2024 |
| Confidence-based design optimization using multivariate kernel density estimation under insufficient input data Y Jung, M Kim, H Cho, W Hu, I Lee Probabilistic Engineering Mechanics, 103702, 2024 | | 2024 |
