| Multiaxial fatigue life prediction of polychloroprene rubber (CR) reinforced with tungsten nano-particles based on semi-empirical and machine learning models J Choi, L Quagliato, S Lee, J Shin, N Kim International Journal of Fatigue 145, 106136, 2021 | 29 | 2021 |
| A new approach to preform design in metal forging processes based on the convolution neural network S Lee, L Quagliato, D Park, I Kwon, J Sun, N Kim Applied Sciences 11 (17), 7948, 2021 | 18 | 2021 |
| Machine learning-based models for the estimation of the energy consumption in metal forming processes I Mirandola, GA Berti, R Caracciolo, S Lee, N Kim, L Quagliato Metals 11 (5), 833, 2021 | 17 | 2021 |
| Extreme gradient boosting-inspired process optimization algorithm for manufacturing engineering applications S Lee, J Park, N Kim, T Lee, L Quagliato Materials & Design 226, 111625, 2023 | 16 | 2023 |
| A buckling instability prediction model for the reliable design of sheet metal panels based on an artificial intelligent self-learning algorithm S Lee, L Quagliato, D Park, GA Berti, N Kim Metals 11 (10), 1533, 2021 | 9 | 2021 |
| A preform design approach for uniform strain distribution in forging processes based on convolutional neural network S Lee, K Kim, N Kim Journal of Manufacturing Science and Engineering 144 (12), 121004, 2022 | 6 | 2022 |
| Using Convolutional Neural Network with Taguchi Parametric Optimization for Knee Segmentation from X-ray Images YJ Kim, SR Lee, JY Choi, KG Kim BioMed Research International 2021, 2021 | 4 | 2021 |
| Gaussian process regression-driven deep drawing blank design method S Lee, Y Lim, L Galdos, T Lee, L Quagliato International Journal of Mechanical Sciences 265, 108898, 2024 | 1 | 2024 |
| 고압 다이캐스팅 공정에서 제품 결함을 사전 예측하기 위한 기계 학습 기반의 공정관리 방안 연구 이승로， 이승철， 한도석， 김낙수 한국주조공학회지 (주조) 41 (6), 521-527, 2021 | | 2021 |
Naksoo Kim서강대 기계공학과 교수Verified email at sogang.ac.kr
