Journals

2024

1. Jaejung Park, Minseon Kim, Heekyu Kim, Jaejun Lee, Inhyo Lee, Haesun Park, Anna Lee, Kyoungmin Min*, and Seungchul Lee*, 2024, "Exploring the Large Chemical Space in Search of Thermodynamically Stable and Mechanically Robust MXenes via Machine Learning," Physical Chemistry Chemical Physics, https://doi.org/10.1039/D3CP06337B.

2. Iljoo Jeong, Hyunsuk Huh, In-Jee Jung*, and Seungchul Lee*, 2024, "Deep Learning-based Approach to Improve the Accuracy of TDOA-based Sound Source Localization," Journal of the Acoustical Society of Korea, 43(2), pp. 178-183, https://doi.org/10.7776/ASK.2024.43.2.178. (in Korean)

3. Jihoon Kim, Jihun Lee, Taewan Kim, Seungchul Lee*, and Chan IL Park*, "Analysis of Spur Gear Vibration Data on Backlash and Prediction of Backlash Based on Deep Learning," Transactions on the Korean Society for Noise and Vibration Engineering, 2024.02, pp. 78-83, https://doi.org/10.5050/KSNVE.2024.34.1.078. (in Korean)

4. Taewan Kim and Seungchul Lee*, 2024, "Deep Learning Integrated Bayesian Health Indicator for Cross-machinery Health Monitoring," Structural Health Monitoring, https://doi.org/10.1177/14759217241227599.

5. Iljoo Jeong, In-Jee Jung*, and Seungchul Lee*, 2024, "Application of Deep Learning for Accurate Source Localization using Sound Intensity Vector," Journal of the Acoustical Society of Korea, 43(1), pp. 72-77, https://doi.org/10.7776/ASK.2024.43.1.072. (in Korean)

2023

6. Changyun Choi, Jongmok Lee, Hyun-Joon Chung, Jaejung Park, Bumsoo Park, Seokman Sohn, and Seungchul Lee*, 2023, "Directed Graph-Based Refinement of Three-Dimensional Human Motion Data using Spatial-Temporal Information," International Journal of Precision Engineering and Manufacturing - Smart Technology (IJPEM-ST), 2(1):33-46, https://doi.org/10.57062/ijpem-st.2023.0094.

7. Jaejun Lee+, Inhyo Lee+, Jaejung Park, Heekyu Kim, Minseon Kim, Kyungmin Min*, and Seungchul Lee*, 2023, "Optimal Surrogate Models for Predicting Elastic Moduli of MOFs via Multiscale Features," Chemistry of Materials, 35(24), 10457–10475, https://doi.org/10.1021/acs.chemmater.3c01885. (+ equally contributed)

8. Iljeok Kim, Sung Wook Kim, Jeongsan Kim, Hyunsuk Huh, Iljoo Jeong, Taegyu Choi, Jeongchan Kim, and Seungchul Lee*, 2023, "Single Domain Generalizable and Physically Interpretable Bearing Fault Diagnosis for Unseen Working Conditions," Expert Systems with Applications, https://doi.org/10.1016/j.eswa.2023.122455.

9. Sebin Lee, Taewan Kim, Seungchul Lee*, and Sung-Ho Hong*, 2023, "Novel Method of Measuring Wear using Deep Learning," Tribology International, https://doi.org/10.1016/j.triboint.2023.109043.

10. Juwon Na+, Jaejun Lee+, Seong-Hoon Kang, Se-Jong Kim, and Seungchul Lee*, 2023, "Label-free Grain Segmentation for Optical Microscopy Images via Unsupervised Image-to-Image Translation," Materials Characterization, https://doi.org/10.1016/j.matchar.2023.113410. (+ equally contributed)

11. Heekyu Kim, Jaejung Park, Minseon Kim, Jajun Lee, Inhyo Lee, Kyoungmin Min*, and Seungchul Lee*, 2023, "Active Learning Platform for Accelerating the Search for High-Voltage Cathode Materials in an Extensive Chemical Space," Journal of Physical Chemistry C, https://doi.org/10.1021/acs.jpcc.3c05812.

12. Keonhyeok Park, Choon-Su Park, Jun Hyeong Park, Hyung Jin Lee, and Seungchul Lee*, 2023, "Deep Learning-Based Conversion of Phased Array Ultrasonic Imaging using U-Net," Journal of the Korean Society for Nondestructive Testing, 43(4), pp. 285-291. (in Korean)

13. Kyung Seok Choi, DoGyeom Park, Jin Su Kim, Dae Young Cheung, Bo-In Lee, Young-Seok Cho, Jin Il Kim, Seungchul Lee and Han Hee Lee*, 2023, "Deep Learning in Negative Small Bowel Capsule Endoscopy Improves Small Bowel Lesion Detection and Diagnostic Yield," Digestive Endoscopy, https://doi.org/10.1111/den.14670.

14. Heekyu Kim+, Hae-Yeon Park+, DoGyeom Park, Sun Im*, and Seungchul Lee*, 2023, "Non-invasive Way to Diagnose Dysphagia by Training Deep Learning Model with Spectrograms," Biomedical Signal Processing and Control, 86, Part B, https://doi.org/10.1016/j.bspc.2023.105259. (+ equally contributed)

15. Mi Hyun Lim+, Seungmin Shin+, Keonhyeok Park, Jaejung Park, Sung Won Kim, Mohammed Abdullah Basurrah, Seungchul Lee*, and Do Hyun Kim*, 2023, "Deep Learning Model for Predicting Airway Organoid Differentiation," Tissue Engineering and Regenerative Medicine, https://doi.org/10.1007/s13770-023-00563-8. (+equally contributed)

16. Juwon Na, Se-Jong Kim, Heekyu Kim, Seong-Hoon Kang, and Seungchul Lee*, 2023, "A Unified Microstructure Segmentation Approach via Human-In-The-Loop Machine Learning," Acta Materialia, 255, https://doi.org/10.1016/j.actamat.2023.119086.

17. Myeong-Seok Go, Jae Hyuk Lim*, and Seungchul Lee, 2023, "Physics-informed Neural Network-based Surrogate Model for a Virtual Thermal Sensor with Real-time Simulation," International Journal of Heat and Mass Transfer, 214(2023), https://doi.org/10.1016/j.ijheatmasstransfer.2023.124392.

18. Hong-Kyun Noh, In-Ho Choi, Jae  Jae Hyuk Lim*, Seungchul Lee, Taejoo Kim, and Deog-Kwan Kim, 2023, "Surrogate Modeling of the Fan Plot of a Rotor System considering Composite Blades using Convolutional Neural Networks with Image Composition," Journal of Computational Design and Engineering, 10(3), 1250-1266, https://doi.org/10.1093/jcde/qwad049.

19. Iljoo Jeong, Soo Young Lee, Keonhyeok Park, Iljeok Kim, Hyunsuk Huh, and Seungchul Lee*, 2023, "Wafer Map Failure Pattern Classification using Geometric Transformation-Invariant Convolutional Neural Network," Scientific Reports, https://doi.org/10.1038/s41598-023-34147-2.

20. Iljeok Kim, Juwon Na, Jong Pil Yun*, and Seungchul Lee*, 2023, "Deep Feature Selection Framework for Quality Prediction in Injection Molding Process," IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2023.3268421.

21. Do-Won Kim, Myeong-Seok Go, Jae Hyuk Lim*, and Seungchul Lee, 2023, "Data-driven Stress and Strain Curves of the Unidirectional Composites by Deep Neural Networks with Principal Component Analysis and Selective-data Augmentation," Composite Structures, 313(1), https://doi.org/10.1016/j.compstruct.2023.116902.

22. Taewi Kim, Insic Hong, Yeonwook Roh, Dongjin Kim, Sung Wook Kim, Sunghoon Im, Changhwan Kim, Kiwon Jang, Seongyeon Kim, Minho Kim, Jieun Park, Dohyeon Gong, Kihyeon Ahn, Jingoo Lee, Gunhee Lee, Hak-Seung Lee, Jeehoon Kang, Ji Man Hong, Seungchul Lee, Sungchul Seo, Bon-Kwon Koo*, Je-sung Koh*, Seungyong Han* and Daeshik Kang*, 2023, "Spider-inspired Tunable Mechanosensor for Biomedical Applications," npj Flexible Electronics, 7(12), https://doi.org/10.1038/s41528-023-00247-2.

23. Jeong Ah Lee, Jaejung Park, Yeon Taek Choi, Rae Eon Kim, Jaimyun Jung*, Seungchul Lee*, Min Hong Seo, and Hyoung Seop Kim*, 2023, "Influence of Tensile Properties on Hole Expansion Ratio Investigated using a Generative Adversarial Imputation Network with Explainable Artificial Intelligence," Journal of Materials Science, https://doi.org/10.1007/s10853-023-08315-8.

24. Sung Wook Kim, Eunji Kwak, Ki-Yong Oh*, and Seungchul Lee*, 2023, "Modeling and Prediction of Lithium-Ion Battery Thermal Runaway via a Multiphysics-Informed Neural Network," Journal of Energy Storage, 60, 106654, https://doi.org/10.1016/j.est.2023.106654.

2022

25. Taewan Kim and Seungchul Lee*, 2022, "A Novel Unsupervised Clustering and Domain Adaptation Framework for Rotating Machinery Fault Diagnosis," IEEE Transactions on Industrial Informatics, 19(9), https://doi.org/10.1109/TII.2022.3228395.

26. Soo Young Lee, Jihun Lee, Joong Seok Lee*, and Seungchul Lee*, 2022, "Deep Learning-based Prediction and Interpretation of Physical Phenomena for Metaporous Materials," Materials Today Physics, 30, 100946, https://doi.org/10.1016/j.mtphys.2022.100946.

27. Hyeonji Kim+, Keonhyeok Park+, Jung-Min Yon+, Sung Won Kim, Soo young Lee, Iljoo Jeong, Jinah Jang*, Seungchul Lee*, and Dong-Woo Cho*, 2022, "Predicting Multipotency of Human Adult Stem Cells Derived from Various Donors through Deep Learning," Scientific Reports, https://doi.org/10.1038/s41598-022-25423-8 (+ equally contributed)

28. Hyunsuk Huh, Jeong-Jung Kim, Doo-Yeol Koh, Chang-Hyun Kim, and Seungchul Lee*, 2022, "Tactile Sensor-based Object Recognition Method Robust to Gripping Conditions Using Fast Fourier Convolution Algorithm,"  Journal of Korea Robotics Society, 17(3), pp. 365-372, https://doi.org/10.7746/jkros.2022.17.3.365 [in Korean].

29. Gyuwon Kim+, Jung Ho Jeon+, Keonhyeok Park, Sung Won Kim, Do Hyun Kim*, and Seungchul Lee*, 2022, "High Throughput Screening of Mesenchymal Stem Cell Lines using Deep Learning," Scientific Reports, 12, 17507 (2022), https://doi.org/10.1038/s41598-022-21653-y. (+ equally contributed)

30. Seongwook Choi+, Jinge Yang+, Soo Young Lee+, Jiwoong Kim, Seungchul Lee*, and Chulhong Kim*, 2022, "Deep Learning Enhances Multiparametric Dynamic Volumetric Photoacoustic Computed Tomography in Vivo (DL-PACT)," Advanced Science, https://doi.org/10.1002/advs.202202089. (+ equally contributed)

31. Yuyeon Jung+, Taewan Kim+, Mi-Ryung Han, Geun Young Kim, Seungchul Lee*, and Youn Jin Choi*, 2021, "Machine Learning Approach of Ovarian Tumor Diagnosis Using Deep Convolutional Neural Networks," Scientific Reports, 12, 17024 (2022), https://doi.org/10.1038/s41598-022-20653-2. (+ equally contributed)

32. Hae-Yeon Park+, DoGyeom Park+, Hye Seon Kang, HyunBum Kim, Seungchul Lee*, and Sun Im*, "Post-stroke Respiratory Complications using Machine Learning with Voice Features from Mobile Devices," Scientific Reports, 12, 16682 (2022), https://doi.org/10.1038/s41598-022-20348-8. (+ equally contributed)

33. Bayu Adhi Tama, Malinda Vania, Seungchul Lee*, and Sunghoon Lim*, 2022, "Recent Advances in the Application of Deep Learning for Fault Diagnosis of Rotating Machinery Using Vibration Signals," Artificial Intelligence Review, https://doi.org/10.1007/s10462-022-10293-3.

34. Hyoungcheol Kwon, Hyunsuk Huh, Hwiwon Seo, Songhee Han, Imhee Won, Jiwoong Sue, Dongyean Oh, Felipe Iza, Seungchul Lee*, Sung Kye Park, and Seonyong Cha, 2022, "TCAD Augmented Generative Adversarial Network for Hot-spot Detection and Mask-layout Optimization in a Large Area HARC Etching Process," Physics of Plasma, https://doi.org/10.1063/5.0093076.

35. Soo Young Lee, Jiho Chang, and Seungchul Lee*, 2022, "Point-level Deep Learning Approach for 3D Acoustic Source Localization," Smart Structures and Systems, 29(6), https://doi.org/10.12989/sss.2022.29.6.000 .

36. Keonhyeok Park+, Jong Young Lee+, Soo Young Lee, Iljoo Jeong, Jin Won Kim, Sun Ah Nam, Hyung Wook Kim*, Seungchul Lee*, Yong Kyun Kim*, 2022, "Deep Learning Predicts the Differentiation of Kidney Organoids Derived from Human Induced Pluripotent Stem Cells," Kidney Research and Clinical Practice, 2022;j.krcp.22.017, https://doi.org/10.23876/j.krcp.22.017. (+ equally contributed)

37. Sung Wook Kim, Ki-Yong Oh*, and Seungchul Lee*, 2022, "Novel Informed Deep Learning-Based Prognostics Framework for On-Board Health Monitoring of Lithium-Ion Batteries," Applied Energy, 315(1), https://doi.org/10.1016/j.apenergy.2022.119011.

38. Soo Young Lee, Jiho Chang*, and Seungchul Lee*, 2022, "Deep Learning-enabled High-resolution and Fast Sound Source Localization in Spherical Microphone Array System," IEEE Transactions on Instrumentation & Measurement, Vol. 71, pp. 1-12, https://doi.org/10.1109/TIM.2022.3161693. 

39. Bayu Adhi Tama, Soo Young Lee, and Seungchul Lee*, 2022, "A Systematic Mapping Study and Empirical Comparison of Data-driven Intrusion Detection Techniques in Industrial Control Networks," Archives of Computational Methods in Engineering, https://doi.org/10.1007/s11831-022-09767-y.

40. Soo Young Lee, Choon-Su Park, Keonhyeok Park, Hyung Jin Lee*, and Seungchul Lee*, 2022, "A Physics-informed and Data-driven Deep Learning Approach for Wave Propagation and its Scattering Characteristics," Engineering with Computers, https://doi.org/10.1007/s00366-022-01640-7.

41. Jongbeom Kim+, Gyuwon Kim+, Lei Li+, Pengfei Zhang, Jin Young Kim, Yeonggeun Kim, Hyung Ham Kim, Lihong V. Wang*, Seungchul Lee*, and Chulhong Kim*, 2022, "Deep Learning Acceleration of Multiscale Superresolution Localization Photoacoustic Imaging," Light: Science & Applications, 11, 131, https://doi.org/10.1038/s41377-022-00820-w. (+ equally contributed)

42. Gyuwon Kim+, Jongbeom Kim+, Woo June Choi*, Chulhong Kim*, and Seungchul Lee*, 2022, "Integrated Deep Learning Framework for Accelerated Optical Coherence Tomography Angiography," Scientific Reports, 12, 1289, https://doi.org/10.1038/s41598-022-05281-0. (+ equally contributed)

43. Sung Wook Kim, Junho Gong, Sang Won Lee*, and Seungchul Lee*, 2022, "Recent Advances of Artificial Intelligence in Manufacturing Industrial Sectors: A Review," International Journal of Precision Engineering and Manufacturing, https://doi.org/10.1007/s12541-021-00600-3 [invited].

2021

44. Sampa Misra, Seungwan Jeon, Ravi Managuli, Seiyon Lee, Gyuwon Kim, Chiho Yoon, Seungchul Lee, Richard G. Barr*, and Chulhong Kim*, 2021, "Bi-modal Transfer Learning for Classifying Breast Cancers via Combined B-mode and Ultrasound Strain Imaging," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69(1), pp. 222-232, 10.1109/TUFFC.2021.3119251. (front cover page)

45. Do-Won Kim, Jae Hyuk Lim*, and Seungchul Lee, 2021, "Prediction and Validation of the Transverse Mechanical Behavior of Unidirectional Composites Considering Interfacial Debonding through Convolutional Neural Networks," Composites Part B: Engineering, https://doi.org/10.1016/j.compositesb.2021.109314.

46. Taewan Kim+, Young Hoon Choi+, Jin Ho Choi, Sang Hyub Lee, Seungchul Lee*, and In Seok Lee*, 2021, "Gallbladder Polyp Classification in Ultrasound Images using a New Ensemble Model," Journal of Clinical Medicine, 10(16), 3585, https://doi.org/10.3390/jcm10163585. (+ equally contributed)

47. Chang Kyo Oh+, Taewan Kim+, Yu Kyung Cho, Dae Young Cheung, Bo‐In Lee, Young‐Seok Cho, Jin Il Kim, Myung‐Gyu Choi, Han Hee Lee*, and Seungchul Lee*, 2021, "Convolutional Neural Network-based Object Detection Model to Identify Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images," Journal of Gastroenterology and Hepatology, https://doi.org/10.1111/jgh.15653. (+ equally contributed)

48. Bayu Adhi Tama, and Seungchul Lee*, 2021, "Comments on Stacking Ensemble based Deep Neural Networks Modeling for Effective Epileptic Seizure Detection," Expert Systems with Applications, https://doi.org/10.1016/j.eswa.2021.115488.

49. Juwon Na, Gyuwon Kim, Seong-Hoon Kang, Se-Jong Kim*, and Seungchul Lee*, 2021, "Deep Learning-based Discriminative Refocusing of Scanning Electron Microscopy Images for Materials Science," Acta Materialia, 214, 116987, https://doi.org/10.1016/j.actamat.2021.116987.

50. Jaimyun Jung+, Juwon Na+, Hyung Keun Park, Jeong Min Park, Gyuwon Kim, Seungchul Lee*, and Hyoung Seop Kim*, 2021, "Super-resolving Material Microstructure Image via Deep Learning for Microstructure Characterization and Mechanical Behavior Analysis," npj Computational Materials, 7(96), https://doi.org/10.1038/s41524-021-00568-8. (+ equally contributed)

51. Soo Young Lee+, Jiho Chang+, and Seungchul Lee*, 2021, "Deep Learning-based Method for Multiple Sound Source Localization with High Resolution and Accuracy," Mechanical Systems and Signal Processing, 161, 107959, https://doi.org/10.1016/j.ymssp.2021.107959. (+ equally contributed)

52. Sung Wook Kim, Seong-Hoon Kang, Se-Jong Kim*, and Seungchul Lee*, 2021, "Estimating the Phase Volume Fraction of Multi-Phase Steel via Unsupervised Deep Learning," Scientific Reports, 11, 5902, https://doi.org/10.1038/s41598-021-85407-y.

53. Sung Wook Kim, Iljeok Kim, Jonghwan Lee, and Seungchul Lee*, 2021, "Knowledge Integration into Deep Learning in Dynamical Systems: An Overview and Taxonomy," Journal of Mechanical Science and Technology, 35(4), https://doi.org/10.1007/s12206-021-0342-5 [invited].

54. Sung Wook Kim, Ki-Yong Oh, and Seungchul Lee*, 2021, "Physics-Informed Neural Network For Estimation Of Lithium-Ion Battery State-of-Health,"  Transactions on the Korean Society for Noise and Vibration Engineering, 31(2), pp. 178-185,  https://doi.org/10.5050/KSNVE.2021.31.2.178 [In Korean].

55. Andrew Glaeser, Soo Young Lee, Yunseob Hwang, Vignesh Selvaraj, Kangsan Lee, Namjeong Lee, Seungchul Lee, and Sangkee Min*, 2021, "Applications of Deep Learning for Fault Detection in Industrial Cold Forging," International Journal of Production Research, https://doi.org/10.1080/00207543.2021.1891318.

56. Yongju Kim, Hyung Keun Park, Jaimyun Jung, Peyman Asghari-Rad, Seungchul Lee, Jin You Kim, Hwan Gyo Jung, and Hyoung Seop Kim*, 2021, "Exploration of Optimal Microstructure and Mechanical Properties in Continuous Microstructure Space using a Variational Autoencoder," Materials & Design, Vol. 202, https://doi.org/10.1016/j.matdes.2021.109544.

57. Gyuwon Kim, Soo Young Lee, Jong-Seok Oh, and Seungchul Lee*, 2021, "Deep Learning-based Estimation of the Unknown Road Profile and State Variables for the Vehicle Suspension System," IEEE Access, 13878-13890, https://doi.org/10.1109/ACCESS.2021.3051619.

58. Yunseob Hwang+, Han Hee Lee+, Chunghyun Park, Bayu Adhi Tama, Jin Su Kim, Dae Young Cheung, Woo Chul Chung, Young-Seok Cho, Kang-Moon Lee, Myung-Gyu Choi, Seungchul Lee*, and Bo-In Lee*, 2021, "Improved Classification and Localization Approach to Small Bowel Capsule Endoscopy Using Convolutional Neural Network," Digestive Endoscopy, 33, pp. 598-607, https://doi.org/10.1111/den.13787. (+ equally contributed)

2020

59. Da Seul Shin, Chi Hun Lee, U. Kühn, Seungchul Lee, Seong Jin Park, H. Schwab, Sergio Scudino and K. Kosiba*, 2020, "Optimizing Laser Powder Bed Fusion of Ti-5Al-5V-5Mo-3Cr by Artificial Intelligence," Journal of Alloys and Compounds, https://doi.org/10.1016/j.jallcom.2020.158018.

60. Soo Young Lee+, Seokyeong Byeon+, Hyoung Seop Kim, Hyungyu Jin*, and Seungchul Lee*, 2020, "Deep Learning-based Phase Prediction of High-entropy Alloys: Optimization, Generation, and Explanation," Materials & Design, https://doi.org/10.1016/j.matdes.2020.109260. (+ equally contributed)

61. HyunBum Kim†, Juhyeong Jeon†, Yeon Jae Han, YoungHoon Joo, Jonghwan Lee, Seungchul Lee* and Sun Im*, 2020, "Convolutional Neural Network Classifies Pathological Voice Change in Laryngeal Cancer with High Accuracy," Journal of Clinical Medicine, 9(11), 3415; https://doi.org/10.3390/jcm9113415. (+ equally contributed)

62. Kyung Ho Sun+, Hyunsuk Huh+, Bayu Adhi Tama, Soo Young Lee, Joon Ha Jung, and Seungchul Lee*, 2020, "Vision-based Fault Diagnostics using Explainable Deep Learning with Class Activation Map," IEEE Access, 10.1109/ACCESS.2020.3009852. (+ equally contributed)

63. Chihun Lee, Juwon Na, Kyongho Park, Hyeonjae Yu, Jongsun Kim, Kwonil Choi, Dongyong Park, Seongjin Park, Junsuk Rho* and Seungchul Lee*, 2020, "Development of Artificial Neural Network System to Recommend Process Conditions of Injection Molding for Various Geometries," Advanced Intelligent Systems, https://doi.org/10.1002/aisy.202000037.

64. Andrew Glaeser, Vignesh Selvaraj, Kangsan Lee, Namjeong Lee, Yunseob Hwang, Sooyoung Lee, Seungchul Lee, and Sangkee Min*, 2020, "Remote Machine Mode Detection in Cold Forging using Vibration Signal," Procedia Manufacturing, Vol. 48, pp. 908-914

65. Bayu Adhi Tama+, Dohyun Kim+, Gyuwon Kim, Soo Whan Kim*, and Seungchul Lee*, 2020, "Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology – Head and Neck Surgery," Clinical & Experimental Otorhinolaryngology, 13(4), pp. 326-339, https://doi.org/10.21053/ceo.2020.00654. (+ equally contributed)

66. Sung Wook Kim, Young Gon Lee, Bayu Adhi Tama, and Seungchul Lee*, 2020, "Reliability-enhanced Camera Lens Module Classification using Semi-supervised Regression Method," Applied Sciences, 10(11), 3832, https://doi.org/10.3390/app10113832.

67. Bayu Adhi Tama, Sun Im, and Seungchul Lee*, 2020, "Improving an Intelligent Detection System for Coronary Heart Disease using a Two-tier Classifier Ensemble," BioMed Research International, Vol. 2020, https://doi.org/10.1155/2020/9816142.

68. Namjeong Lee, Sungmin Kim, Iljoo Jeong, Seokman Sohn, and Seungchul Lee*, 2020, "Ensemble Method of Rule-Based and Deep Learning for Rotating Machine Diagnostics," Transactions on the Korean Society for Noise and Vibration Engineering. [In Korean]

69. Kangsan Lee, Juwon Na, Jongduk Sohn, Seokman Sohn, and Seungchul Lee*, 2020, "Image Recognition Algorithm for Maintenance Data Digitization: CNN and FCN," Transactions on the Korean Society for Noise and Vibration Engineering. [In Korean]

70. Jeong-Won Lee, Seongmin Kim, Seungchul Lee, and Woonbong Hwang*, 2020, "Exponential Promotion and Suppression of Bubble Nucleation in Carbonated Liquid by Modification of Surface Wettability," Applied Surface Science, Vol. 512, https://doi.org/10.1016/j.apsusc.2020.145709.

71. Soo Young Lee, Bayu Adhi Tama, Changyun Choi, Jeong Yeon Hwang, Jonggeun Bang, and Seungchul Lee*, 2020, "Spatial and Sequential Deep Learning Approach for Predicting Temperature Distribution in a Steel-making Continuous Casting Process," IEEE Access, 8(1), pp. 2169-3536, 10.1109/ACCESS.2020.2969498.

2019

72. Soo Young Lee, Bayu Adhi Tama, Seok Jun Moon, and Seungchul Lee*, 2019, "Steel Surface Defect Diagnostics using Deep Convolutional Neural Network and Class Activation Map," Applied Sciences, 9(24), 5449, https://doi.org/10.3390/app9245449.

73. Gi Woung Song, Bayu Adhi Tama, Jaewan Park, Jeong Yeon Hwang, Jonggeun Bang, Seong Jin Park, and Seungchul Lee*, 2019, "Temperature Control Optimization in a Steel‐Making Continuous Casting Process Using Multimodal Deep Learning Approach," Steel Research International, https://doi.org/10.1002/srin.201900321. [Top Downloaded Paper 2018-2019]

74. Woosung Choi+, Hyunsuk Huh+, Bayu Adhi Tama, Gyusang Park, and Seungchul Lee*, 2019, "A Neural Network Model for Material Degradation Detection and Diagnosis Using Microscopic Images," IEEE Access, 7, pp.92151-92160. (+ equally contributed)

75. Juhyeong Jeon, Yeon Jae Han, Geun-Young Park, Deung Gyun Sohn, Seungchul Lee*, and Sun Im*, 2019, "Artificial Intelligence in the Field of Electrodiagnosis – A New Threat or Heralding a New Era in Electromyography?," Clinical Neurophysiology, 130(10), https://doi.org/10.1016/j.clinph.2019.06.005.

76. D. Shin, C. Lee, S. Kim, D. Park, J. Oh, C. Gal, J. Koo, S. Park and S. Lee*, 2019, "Analysis of Cold Compaction for Fe-C, Fe-C-Cu Powder Design based on Constitutive Relation and Artificial Neural Networks," Powder Technology, 353, https://doi.org/10.1016/j.powtec.2019.05.042.

2018

77. B. Park, H. Jeong, H. Huh, M. Kim and S. Lee*, 2018, "Experimental Study on the Life Prediction of Servo Motors through Model-based System Degradation Assessment and Accelerated Degradation Testing," Journal of Mechanical Science and Technology, 32(11), 5105-5110.

78. S. Park, H. Jeong and S. Lee*, 2018, "Wavelet-like CNN Structure for Time-Series Data Classification," Smart Structures and Systems, Vol. 22, No. 2 (2018) 175-183.

79. H. Jeong, B. Park, S. Park, and S. Lee*, 2018, "Fault Detection and Identification Method using Observer-based Residuals," Reliability Engineering and System Safety, Vol. 184, pp 27-40.

2017 and Before

80. S. Kim, S. Park, S. Woo, and S. Lee*, 2017, "Development and Analysis of the Interchange Centrality Evaluation Index using Network Analysis," J. Korean Soc. Transp. Vol.35, No.6, pp.525-544. [in Korean]

81. H. Jeong, S. Kim, S. Woo, S. Kim and S. Lee*, 2017, "Real-time Monitoring System for Rotating Machinery with IoT-based Cloud Platform," Transactions of the KSME A. [in Korean]

82. H. Jeong, S. Park , S. Woo, and S. Lee*, 2016, "Rotating Machinery Diagnostics Using Deep Learning on Orbit Plot Images," Procedia Manufacturing, Vol. 5, pp. 1107-1118.

83. L. Cui, Y. Zhang, F. Zhang*, J. Zhang, and S. Lee, 2016, "Vibration Response Mechanism of Faulty Outer Race Rolling Element Bearings for Quantitative Analysis," Journal of Sound and Vibration, 364, pp. 67-76.

84. Z. Zhang, S. Wu*, L. Binfeng, and S. Lee, 2015, "(n,N) Type Maintenance Policy for Multi-component Systems with Failure Interactions," International Journal of Systems Science, 46(6), pp. 1051-1064.

85. Z. Zhang, S. Wu, S. Lee*, and J. Ni, 2014, "Modified Iterative Aggregation Procedure for Maintenance Optimization of Multi-component Systems with Failure Interaction," International Journal of Systems Science, 45(12), pp. 2480-2489.

86. A. Almuhtady, S. Lee*, E. Romeijn, M. Wynblatt, and J. Ni, 2014, "A Degradation-Informed Battery Swapping Policy for Fleets of Electric or Hybrid-Electric Vehicles," Transportation Science, 48(4), pp. 609-618.

87. W. Cheng, Z. Zhang*, S. Lee, and Z. He, 2014, "Investigations of Denoising Source Separation Technique and Its Application to Source Separation and Identification of Mechanical Vibration Signals," Journal of Vibration and Control, 20(14), pp. 2100-2117.

88. L. Cui*, J. Wang, S. Lee, 2014, "Matching Pursuit of an Adaptive Impulse Dictionary for Bearing Fault Diagnosis," Journal of Sound and Vibration, 333(10), pp. 2840-2862.

89. S. Lee, J. Ko, X. Tan, I. B. Patel, R. Balkrishnan, J. Chang*, 2014, "Markov Chain Modeling and Analysis of HIV/AIDS Progression: A Race-based Forecast in the United States," Indian Journal of Pharmaceutical Sciences, 76(2), pp. 107-115.

90. Zhang, S. Wu, L. Binfeng, and S. Lee*, 2013, "Optimal Maintenance Policy for Multi-Component Systems under Markovian Environment Changes," Expert Systems With Applications, 40(18), pp. 7391-7399.

91. S. Lee*, X. Gu, M. Garcellano, M. Diederichs, and J. Ni, 2013, "Discovery of Hidden Opportunities in Manufacturing Systems: MOW and GMOW," International Journal of Advanced Manufacturing Technology, 68(9), pp. 2611-2623.

92. S. Lee*, X. Gu, and J. Ni, 2013, "Stochastic Maintenance Opportunity Windows for Unreliable Two-Machine One-Buffer System," Expert Systems With Applications, 40(13), pp. 5385-5394.

93. X. Gu, S. Lee*, X. Liang, M. Garcellano, M. Diederichs, and J. Ni, 2013, "Hidden Maintenance Opportunities in Discrete and Complex Production Lines," Expert Systems with Application, 40(11), pp. 4353-4361.

94. S. Lee, L. Li*, and J. Ni, 2013, "Markov-based Maintenance Planning Considering Repair Time and Periodic Inspection," ASME Journal of Manufacturing Science and Engineering, 135(3), 031013 (12 pages), DOI:10.1115/1.4024152

95. S. Lee* and J. Ni, 2012, "Joint Decision Making for Maintenance and Production Scheduling of Production Systems," International Journal of Advanced Manufacturing Technology, 66(5-8), pp. 1135-1146.

96. W. Cheng, S. Lee, Z. Zhang*, and Z. He, 2012, "Independent Component Analysis based Source Number Estimation and Its Comparison for Mechanical Systems," Journal of Sound and Vibration, 331(2012), pp. 5153-5167.

97. S. Lee* and J. Ni, 2012, "Genetic Algorithm for Job Scheduling with Maintenance Consideration in Semiconductor Manufacturing Process," Mathematical Problems in Engineering, Volume 2012, Article ID 875641, 16 pages, DOI:10.1155/2012/875641.

98. W. Cheng, Z. Zhang*, S. Lee, and Z. He, 2011, "Source Contribution Evaluation of Mechanical Vibration Signals via Enhanced Independent Component Analysis," ASME Journal of Manufacturing Science and Engineering, 134(2), pp. 021014 (9 pages).

99. S. Lee, L. Li*, and J. Ni, 2010, "Online Degradation Assessment and Adaptive Fault Detection Using Modified Hidden Markov Model," ASME Journal of Manufacturing Science and Engineering, 132(2), pp. 021010-11.

Submitted 

1. Sung Ho Hong*, Sebin Lee, and Seungchul Lee*, "New Evaluation of Wear Volume Based on Wear Scars Using Deep Learning," submitted

2. Jongmok Lee+, Seungmin Shin+,  Taewan Kim, Bumsoo Park, Changhwan Lee, Insoo Ye, Ho Choi, Anna Lee, Minseok Choi* and Seungchul Lee*, "Re-initialization Strategy for Physics-informed Neural Networks in Fluid Flow Analysis," submitted (+ equally contributed).

3. Inhyo Lee, Jaejun Lee, Minseon Kim, Jaejung Park, Heekyu Kim, Seungchul Lee*, and Kyoungmin Min*, 2023, "Uncovering the Relationship between Metal Elements and Mechanical stability in Metal-Organic Framework," submitted.

4. Hyunsuk Huh+, Iljoo Jeong+, Anna Lee, Seungchul Lee*, and Young-Sik Shin*, 2023, "ABC-HF: Leveraging Falling Acceleration and Body Part Clustering for Physics-based Human Fall Detection with mmWave," under revision. (+ equally contributed)

5. Taewan Kim, Seungmin Shin, Jongmok Lee, Changhwan Lee, Insoo Ye, Ho Choi, and Seungchul Lee*, 2023, "A Physics-informed Convolutional Framework for Digital Twins: Fast Interpolation of Numerical Simulations" submitted.

6. Inmo Yeon+, Iljoo Jeong+, Seungchul Lee* and Jung-woo Choi*, 2023, "EchoScan: Scanning Complex Indoor Geometries via Acoustic Echoes" submitted. (+ equally contributed)

In Preparation

7. Iljoo Jeong+, Hyunsuk Huh+, Bumsoo Park, Anna Lee, In-Jee Jung*, and Seungchul Lee*, 2023, "MicGraphNet: Microphone Graph Network for Cross Correlation-based Time Delay Estimation for Accurate Sound Source Localization," in preparation (+ equally contributed).

8. Iljoo Jeong, Bumsoo Park, Keonhyuk Park, Anna Lee, In-Jee Jung*, and Seungchul Lee*, 2023, "Dual-port Conditional Invertible Neural Network for Sound Intensity Compensation in Sound Source Localization," in preparation.

9. Keonhyeok Park, Soo Young Lee, Iljoo Jeong, Joon Hyung Park, Hyung Jin Lee, Choon-Su Park*, and Seungchul Lee*, 2023, "Deep Learning-based Image Translation for High-Quality and Fast Phased Array Ultrasonic Imaging," in preparation.

10. Jongmok Lee, Seungmin Shin, Taewan Kim, Changhwan Lee, Insoo Ye, Ho Choi, Jae Hyuk Lim, Minseok Choi* and Seungchul Lee*, "Extended Multiphysics-informed Neural Network for Conjugate Heat Transfer Problems," in preparation.

11. Jihun Lee, Soo Young Lee, Joongseok Lee*, and Seungchul Lee*, 2022, "Inverse Design of Metaporous Layers using Conditional Generative Adversarial Network," in preparation.

12. Jaejung Park, Heekyu Kim, Jaejun Lee, Haesun Park*, and Seungchul Lee*, 2023, "Thermodynamically Stable MXenes Identified by the First Principle Calculation Combined with Active Learning," in preparation.

Registered

1. 세포 선별 장치 및 방법, 김도현/김성원/곽승기/전정호/이재선/이승철/김규원, 대한민국, 2022년 8월 30일, 10-2439411 (미국 출원 중, PCT/KR2021/017471)

2. 인공지능 신경망을 이용한 고해상도 음원지도 취득 및 분석방법 및 시스템, 장지호/이승철/이수영, 2022년 6월 23일, 대한민국, 10-2414021, (비즈웨이브 주식회사로 25,000천원 기술이전, 유럽/미국 출원 중, PCT/KR2021/006616)

3. 캡슐 내시경 영상 판독 시스템 및 방법, 이한희/이승철/황윤섭, 2022년 2월 3일, 대한민국, 10-2359984 (미국 출원 중, PCT/KR2021/004735)

4. 인공지능 기반 캡슐 내시경 영상 판독 방법 및 시스템, 이한희/이승철, 2021년 2월 24일, 대한민국, 10-2221943 

5. 음성 및 연하 장애를 유발하는 질환 진단 및 그 판단 방법, 임선/이승철/전주형/주영훈/한연재, 2021년 2월 8일, 대한민국, 10-2216160 (미국 출원 중, PCT/KR2021/002651)

Filed

6. 담낭 용종 판단 시스템 및 그 방법, 이인석/최영훈/이승철/김태완, 대한민국, 2022년 1월 24일 출원, 10-2022-0010235

7. 오가노이드 선별 장치 및 방법, 김도현/이승철/김성원/임미현/박건혁/신승민, 대한민국, 2022년 2월 21일 출원, 10-2022-0022545

8. 신경망 학습부 및 이를 포함하는 개선된 음원지도 제공 시스템, 장지호/조완호/이승철/이수영, 대한민국, 2022년 4월 8일 출원, 10-2022-0043976

9. 난소 종양 분류 방법 및 장치, 최윤진/이승철/김태완/정유연, 대한민국, 2022년 12월 2일 출원, 10-2022-0167068

10. 가상의 데이터 생성을 통한 자동 고장 진단 장치 및 그 작동 방법, 이승철/김민호/신민철, 대한민국, 2022년 12월 17일 출원, 10-2022-0170093

11. 인공지능 기반 고장 특성 조작을 이용한 설비의 정상 신호로부터 고장 신호 생성 기술, 이승철/박형식/이지훈, 대한민국, 2023년 5월 8일 출원, 10-2023-0059375

12. 딥러닝을 이용한 볼의 마모량 측정 방법, 홍성호/이승철/이세빈/김태완, 대한민국, 2023년 5월 9일 출원, 10-2023-0059936

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