Journals 

International Journals

1. Jongmok Lee+, Seungmin Shin+,  Taewan Kim, Bumsoo Park, Ho Choi, Anna Lee, Minseok Choi* and Seungchul Lee*, "Physics Informed Neural Networks for Fluid Flow Analysis with Repetitive Parameter Initialization," 2025, accepted for publication in Scientific Reports (+ equally contributed).

2. Taewan Kim and Seungchul Lee*, "Deep Learning Integrated Bayesian Health Indicator for Cross-machine Health Monitoring," Structural Health Monitoring, 2024, vol. 23, no. 6, pp. 3416-3429. [IF 5.7, JCR 92.0 %]
   https://doi.org/10.1177/14759217241227599

3. Sebin Lee, Taewan Kim, Seungchul Lee*, and Sung-Ho Hong*, "Novel Method for Measuring a Wear Scar Using Deep Learning," Tribology International, 2023, vol. 190, pp. 109043. [IF 6.1, JCR 94.8 %]
   https://doi.org/10.1016/j.triboint.2023.109043 

4. Taewan Kim and Seungchul Lee*, "A Novel Unsupervised Clustering and Domain Adaptation Framework for Rotating Machinery Fault Diagnosis," IEEE Transactions on Industrial Informatics, 2023, vol. 19, no. 9, pp. 9404-9412. [IF 11.7, JCR 98.5 %]
   https://doi.org/10.1109/TII.2022.3228395 

5. Yuyeon Jung+, Taewan Kim+, Mi-Ryung Han, Geun Young Kim, Seungchul Lee*, and Youn Jin Choi*, “Ovarian Tumor Diagnosis Using Deep Convolutional Neural Networks and a Denoising Convolutional Autoencoder,” Scientific Reports, 2022, vol. 12, no. 1, pp. 17024. (+ equally contributed) [IF 4.6, JCR 70.5 %]
   https://doi.org/10.1038/s41598-022-20653-2 

6. Taewan Kim+, Young Hoon Choi+, Jin Ho Choi, Sang Hyub Lee, Seungchul Lee*, and In Seok Lee*, "Gallbladder Polyp Classification in Ultrasound Images using an Ensemble Convolutional Neural Network Model," Journal of Clinical Medicine, 2021, vol. 10, no. 16, pp. 3585. (+ equally contributed) [IF 4.96, JCR 68.3 %]
   https://doi.org/10.3390/jcm10163585 

7. 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*, “Convolutional Neural Network‐based Object Detection Model to Identify Gastrointestinal Stromal Tumors in Endoscopic Ultrasound Images,” Journal of Gastroenterology and Hepatology, 2021, vol. 36, no. 12, pp. 3387-3394. (+ equally contributed) [IF 4.37, JCR 54.3 %]
   https://doi.org/10.1111/jgh.15653 

Domestic Journals

1. 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. (in Korean) https://doi.org/10.5050/KSNVE.2024.34.1.078.  

Submitted 

• Taewan Kim, Seungmin Shin, Jongmok Lee, Changhwan Lee, Insoo Ye, Ho Choi, Minseok Choi, and Seungchul Lee*, "Physics-informed Convolutional Framework for Digital Twins: Fast and Accurate Approximation of Numerical Simulation," under revision

In Preparation 

Conferences

International Conferences

1. Taewan Kim and Seungchul Lee, 2023, "Fully Unsupervised Defect Clustering using Adversarial Autoencoder and Bayesian Mixture Model," PHMAP 2023, Tokyo, Japan.

2. Taewan Kim, Jaejung Park, Sebin Lee, and Seungchul Lee, 2023, "Multi-Agent Deep Reinforcement Learning for Efficient Traffic Signal Control," 20th International Conference on Ubiquitous Robots (UR), Honolulu, USA.

3. Taewan Kim and Seungchul Lee, 2021, "Deep Learning-based Bearing Health Indicator Construction using Baye's Theorem," PHMAP 2021, Jeju, Republic of Korea.

4. Taewan Kim and Seungchul Lee, 2021, "Deep Learning-based Health Indicator for Better Bearing RUL Prediction," 50th International Congress and Exposition on Noise Control Engineering. (online)

Domestic Conferences

1. 이세빈, 김태완, 이승철, 홍성호, 2023, "딥러닝 기반 마모 흔적 측정 방법," 한국트라이볼로지학회 추계학술대회, 경주.

2. 이지훈, 김태완, 박형식, 이승철, 2023, "디지털 전환을 위한 필요조건: 가상 데이터 생성과 시뮬레이션 계산 가속화," 한국소음진동공학회 추계학술대회, 여수.

3. 김태완, 신승민, 이종목, 이창환, 예인수, 최호, 이승철, 2023, "빠른 수치 시뮬레이션 보간을 위한 물리지식기반 컨볼루션 프레임워크," 대한기계학회 CAE 및 응용역학 부문 춘계학술대회, 부산.

4. 신승민, 이종목, 김태완, 이창환, 예인수, 최호, 이승철, 2023, "유동 해석을 위한 물리기반 인공신경망 재초기화 전략," 대한기계학회 CAE 및 응용역학 부문 춘계학술대회, 부산.

5. 이종목, 신승민, 김태완, 이승철, 2023, "물성 변화를 고려한 이중 열 교환 모사 물리기반 인공지능," 대한기계학회 CAE 및 응용역학 부문 춘계학술대회, 부산.

6. 김태완, 이승철, 2022, "다중 좌표계를 이용한 물리기반 인공지능," 대한기계학회 CAE 및 응용역학 부문 춘계학술대회, 부산.

7. 신승민, 이지훈, 김태완, 최호, 이승철, 2022, "원형 실린더 주변의 비정상 층류 유동 해석을 통한 물리기반 인공지능 고찰," 대한기계학회 CAE 및 응용역학 부문 춘계학술대회, 부산.

8. 김태완, 이승철, 2021, "적대적 오토인코더와 가우시안 혼합 모델을 활용한 비지도 결함 클러스터링," 한국소음진동공학회 추계학술대회, 제주.

9. 김태완, 이승철, 2021, "적대적 오토인코더를 활용한 베어링 건강 지표 추출," 대한기계학회 신뢰성부문 춘계학술대회, 제주.

10. 김태완, 황윤섭, 이한희, 이승철, 2020, “딥러닝 기반 소장캡슐내시경 스마트 판독 시스템,” 한국PHM학회 정기학술대회, 서울.

Awards

• The Best Doctoral Thesis Award at the CAE and Applied Mechanics Division of the Korean Society of Mechanical Engineers (KSME) Conference, 2024 

• The Best Paper Award at the Korean Society of Mechanical Engineers (KSME) Conference, 2023

• Second place in the Asia - East and Oceania - Student Category of the steelChallenge-17, World Steel Association, 2022

Patents 

• (등록) 딥러닝을 이용한 볼의 마모량 측정 방법, 홍성호/이승철/이세빈/김태완, 대한민국, 2024/02/26, 1026424500000

• (등록) 담낭 용종 판단 시스템 및 그 방법, 이인석/최영훈/이승철/김태완, 대한민국, 2024/09/30, 1027138050000