Ikjin Lee

Ikjin Lee

KAIST

H-index: 32

Asia-South Korea

About Ikjin Lee

Ikjin Lee, With an exceptional h-index of 32 and a recent h-index of 27 (since 2020), a distinguished researcher at KAIST, specializes in the field of Simulation-based design under uncertainties.

His recent articles reflect a diverse array of research interests and contributions to the field:

A survey on design optimization of battery electric vehicle components, systems, and management

An effective active learning strategy for reliability-based design optimization under multiple simulation models

Uncertainty‐oriented thermoelastic topology optimization with stress constraint

Modified structure of deep neural network for training multi-fidelity data with non-common input variables

Consecutive adaptive Kriging method for high-dimensional reliability analysis based on multi-fidelity framework

A comprehensive multi-fidelity surrogate framework based on Gaussian process for datasets with heterogeneous responses

A novel sampling method for adaptive gradient-enhanced Kriging

Surrogate model-based method for reliability-oriented buckling topology optimization under random field load uncertainty

Ikjin Lee Information

University

Position

Associate Professor of Mechanical Engineering

Citations(all)

3839

Citations(since 2020)

2570

Cited By

2196

hIndex(all)

32

hIndex(since 2020)

27

i10Index(all)

76

i10Index(since 2020)

70

Email

University Profile Page

KAIST

Google Scholar

View Google Scholar Profile

Ikjin Lee Skills & Research Interests

Simulation-based design under uncertainties

Top articles of Ikjin Lee

Title

Journal

Author(s)

Publication Date

A survey on design optimization of battery electric vehicle components, systems, and management

Erdem Acar

Naman Jain

Palaniappan Ramu

Chulhyun Hwang

Ikjin Lee

2024/3

An effective active learning strategy for reliability-based design optimization under multiple simulation models

Structural Safety

Seonghyeok Yang

Mingyu Lee

Yongsu Jung

Hyunkyoo Cho

Weifei Hu

...

2024/3/1

Uncertainty‐oriented thermoelastic topology optimization with stress constraint

International Journal for Numerical Methods in Engineering

Changzheng Cheng

Bo Yang

Xuan Wang

Ikjin Lee

2024

Modified structure of deep neural network for training multi-fidelity data with non-common input variables

Journal of Mechanical Design

Hwisang Jo

Byeong-uk Song

Joon-Yong Huh

Seung-Kyu Lee

Ikjin Lee

2024/10

Consecutive adaptive Kriging method for high-dimensional reliability analysis based on multi-fidelity framework

Structural and Multidisciplinary Optimization

Youngseo Park

Ikjin Lee

2024/1

A comprehensive multi-fidelity surrogate framework based on Gaussian process for datasets with heterogeneous responses

Knowledge-Based Systems

Juyoung Lee

Mingyu Lee

Bong Jae Lee

Ikjin Lee

2024/7

A novel sampling method for adaptive gradient-enhanced Kriging

Computer Methods in Applied Mechanics and Engineering

Mingyu Lee

Yoojeong Noh

Ikjin Lee

2024/1/1

Surrogate model-based method for reliability-oriented buckling topology optimization under random field load uncertainty

Structures

Bo Yang

Xuan Wang

Changzheng Cheng

Ikjin Lee

Zongjun Hu

2024/5/1

Fe-Ni-Cr Diffusion Barrier for High-temperature Operation of Bi2Te3

Journal of Alloys and Compounds

Sang Hyun Park

Yeongseon Kim

Hanhwi Jang

ChulHyun Hwang

Jaejoon Choi

...

2023/1

A nonlinearity integrated bi-fidelity surrogate model based on nonlinear mapping

Structural and Multidisciplinary Optimization

Kunpeng Li

Qingye Li

Liye Lv

Xueguan Song

Yunsheng Ma

...

2023/9

Surrogate-Based Time-Dependent Reliability Analysis for a Digital Twin

Journal of Mechanical Design

Weifei Hu

Jiquan Yan

Feng Zhao

Chen Jiang

Hongwei Liu

...

2023/6/2

Distribution estimation of Johnson-Cook parameters considering correlation in quasi-static state

International Journal of Mechanical Sciences

Jeonghwan Choo

Yongsu Jung

Hwisang Jo

Juhaing Kim

Ikjin Lee

2023/4/15

A new sampling approach for system reliability-based design optimization under multiple simulation models

Reliability Engineering & System Safety

Seonghyeok Yang

Mingyu Lee

Ikjin Lee

2023/3/1

A new framework for efficient sequential sampling-based RBDO using space mapping

Journal of Mechanical Design

Jeong Woo Park

Ikjin Lee

2023/3

Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review

Junhyeong Lee

Donggeun Park

Mingyu Lee

Hugon Lee

Kundo Park

...

2023/8/4

Statistical Model Calibration and Design Optimization under Aleatory and Epistemic Uncertainty

Reliability Engineering & System Safety

Yongsu Jung

Hwisang Jo

Jeonghwan Choo

Ikjin Lee

2022/2/27

Modeling of geometric uncertainties in topology optimization via the shift of design nodes

Structural and Multidisciplinary Optimization

Jonghyun Kim

Ikjin Lee

2022/7

Idle vehicle relocation strategy through deep learning for shared autonomous electric vehicle system optimization

Journal of Cleaner Production

Seongsin Kim

Ungki Lee

Ikjin Lee

Namwoo Kang

2022/1/20

Deep generative tread pattern design framework for efficient conceptual design

Journal of Mechanical Design

Mingyu Lee

Youngseo Park

Hwisang Jo

Kibum Kim

Seungkyu Lee

...

2022/7/1

A reanalysis-based multi-fidelity (RBMF) surrogate framework for efficient structural optimization

Computers & Structures

Mingyu Lee

Yongsu Jung

Jaehoon Choi

Ikjin Lee

2022/12/1

See List of Professors in Ikjin Lee University(KAIST)

Co-Authors

H-index: 60
KK Choi

KK Choi

University of Iowa

H-index: 54
Sung Jin Kim

Sung Jin Kim

KAIST

H-index: 52
Byeng Dong Youn

Byeng Dong Youn

Seoul National University

H-index: 46
Behrooz Keshtegar

Behrooz Keshtegar

University of Zabol

H-index: 39
Bong Jae Lee

Bong Jae Lee

KAIST

H-index: 39
Jiong Tang

Jiong Tang

University of Connecticut

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