232 Gongneung-ro, Nowon-gu, Seoul, 01811, korea
Tel :+82-2-970-6793
Fax : +82-2-970-6800
Copyright © Seoul National University of Science&Technology. All rights Reserved.
Department of Data Science
Name |
Jaewoong Shim |
MAJOR |
Data Mining, Manufacturing Data Analysis, Quality Analysis |
TEL |
02-970-6485 |
E-mail |
jaewoong@seoultech.ac.kr |
Biography
◾ 2021 Ph.D., Industrial Engineering, Seoul National University (Data Mining)
◾ 2016 M.S., Industrial Engineering, Seoul National University (Data Mining)
◾ 2014 B.S., Industrial Engineering, Seoul National University
◾ 2016 M.S., Industrial Engineering, Seoul National University (Data Mining)
◾ 2014 B.S., Industrial Engineering, Seoul National University
Careers
◾ AI team lead, RTM
◾ Engineer, Quality Assurance, Memory Business, Samsung Electronics
◾ Engineer, Quality Assurance, Memory Business, Samsung Electronics
Research Areas
◾ Machine learning and deep learning techniques including
- Anomaly detection
- Cost-effective learning
- Active learning
- Adaptive learning
- Explainable model
◾ Real-world applications
- Fault detection and diagnosis for manufacturing systems
- Quality control
- Fraud detection
- Health care
- Anomaly detection
- Cost-effective learning
- Active learning
- Adaptive learning
- Explainable model
◾ Real-world applications
- Fault detection and diagnosis for manufacturing systems
- Quality control
- Fraud detection
- Health care
Journal Papers
◾ Jaewoong Shim, Seokho Kang* (2022), “Domain-Adaptive Active Learning for Cost-effective Virtual Metrology Modeling”, Computers in Industry, 135: 103572.
◾ Jaewoong Shim, Sungzoon Cho*, Euiseok Kum, Suho Jung (2021), “Adaptive Fault Detection Framework for Recipe Transition in Semiconductor Manufacturing”, Computers & Industrial Engineering, 161: 107632.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2021), “Active inspection for cost-effective fault prediction in manufacturing process”, Journal of Process Control, 105: 250-258.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2021), “Active cluster annotation for wafer map pattern classification in semiconductor manufacturing”, Expert Systems with Applications, 183: 115429.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2020), “Active learning of convolutional neural network for cost-effective wafer map pattern classification”, IEEE Transactions on Semiconductor Manufacturing, 33 (2): 258-266.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Wonsang Chang, Sungzoon Cho* (2018), “Product failure prediction with missing data”, International Journal of Production Research, 56 (14): 4849-4859.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho*, Wonsang Chang, Junhwan Kim (2017), “Mining the relationship between production and customer service data for failure analysis of industrial products”, Computers & Industrial Engineering, 106: 137-146
◾ Jaewoong Shim, Sungzoon Cho*, Euiseok Kum, Suho Jung (2021), “Adaptive Fault Detection Framework for Recipe Transition in Semiconductor Manufacturing”, Computers & Industrial Engineering, 161: 107632.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2021), “Active inspection for cost-effective fault prediction in manufacturing process”, Journal of Process Control, 105: 250-258.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2021), “Active cluster annotation for wafer map pattern classification in semiconductor manufacturing”, Expert Systems with Applications, 183: 115429.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho* (2020), “Active learning of convolutional neural network for cost-effective wafer map pattern classification”, IEEE Transactions on Semiconductor Manufacturing, 33 (2): 258-266.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Wonsang Chang, Sungzoon Cho* (2018), “Product failure prediction with missing data”, International Journal of Production Research, 56 (14): 4849-4859.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho*, Wonsang Chang, Junhwan Kim (2017), “Mining the relationship between production and customer service data for failure analysis of industrial products”, Computers & Industrial Engineering, 106: 137-146
◾ Learning from single-defect wafer maps to classify mixed-defect wafer maps, EXPERT SYSTEMS WITH APPLICATIONS, vol.233, 2023심재웅
◾ Deep Learning Model for Robust Target Tracking Using TDoA Probabilistic Image, 한국통신학회논문지, vol.48 No.7 pp.807~815, 2023심재웅
◾ Domain-adaptive active learning for cost-effective virtual metrology modeling, Computers in industry, vol.135, 2022심재웅
◾ Adaptive fault detection framework for recipe transition in semiconductor manufacturing, Computers & industrial engineering, vol.161, 2021심재웅
◾ Active inspection for cost-effective fault prediction in manufacturing process, Journal of process control, vol.105 pp.250~258, 2021심재웅
◾ Active cluster annotation for wafer map pattern classification in semiconductor manufacturing, Expert systems with applications, vol.183, 2021심재웅
◾ Active Learning of Convolutional Neural Network for Cost-Effective Wafer Map Pattern Classification, IEEE transactions on semiconductor manufacturing, vol.33 No.2 pp.258~266, 2020심재웅
Conference Papers
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, “Kernel rotation forests for classification”, The 1st International Workshop on Conceptual Modeling for Big Data and Smart Computing–2020 IEEE International Conference on Big Data and Smart Computing, Feb 2020, Busan, Korea.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, “Cost-effective construction of convolutional neural network for wafer map pattern classification”, 2019 INFORMS Annual Meeting, Oct 2019, Seattle, WA, USA.
◾ Hyung-Seok Kang, Jaewoong Shim, Kil Soo Kim, Seung Hoon Tong, “Defect classification using ensemble convolutional neural network in semiconductor manufacturing”, 2018 INFORMS Annual Meeting, Nov 2018, Phoenix, AZ, USA.
◾ Jaewoong Shim, Chanwhi Jung, Jinsik Kim, Doh Soon Kwak, Kunhan Kim, Seung Hoon Tong, “Prioritize interaction effects on wafer defects for multistage semiconductor fabrication based on applied association rule mining”, 2018 INFORMS Annual Meeting, Nov 2018, Phoenix, AZ, USA.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Active inspection for cost-effective fault prediction in manufacturing process", 2019 Fall Conference of Korean Institute of Industrial Engineers (KIIE), Nov 2019, Seoul, Korea.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Active learning of convolutional neural networks for cost-effective wafer map pattern classification", 2019 Spring Conference of Korean Institute of Industrial Engineers (KIIE), Apr 2019, Gwangju, Korea.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho, “Identifying the cause of product defects using after-sales service data”, 2015 Fall Conference of Korea Data Mining Society (KDMS), Nov 2015.
◾ Jaewoong Shim, Sungzoon Cho, “Expanding Minority Area: Oversampling method in imbalanced data classification”, 2015 Spring Conference of Korea Business Intelligence Data Mining Society (KDMS), April 2015.
◾ Jaewoong Shim, Eunji Kim, Seokho Kang, Sungzoon Cho, "Hybrid approach with centroid based classification and SVM for multi-class text classification", 2014 Fall Conference of Korea Business Intelligence Data Mining Society (KDMS), Nov 2014.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Improving the accuracy of rotation forest using kernel PCA", 2014 Spring Joint Conference of Korean Institute of Industrial Engineers (KIIE), May 2014.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, “Cost-effective construction of convolutional neural network for wafer map pattern classification”, 2019 INFORMS Annual Meeting, Oct 2019, Seattle, WA, USA.
◾ Hyung-Seok Kang, Jaewoong Shim, Kil Soo Kim, Seung Hoon Tong, “Defect classification using ensemble convolutional neural network in semiconductor manufacturing”, 2018 INFORMS Annual Meeting, Nov 2018, Phoenix, AZ, USA.
◾ Jaewoong Shim, Chanwhi Jung, Jinsik Kim, Doh Soon Kwak, Kunhan Kim, Seung Hoon Tong, “Prioritize interaction effects on wafer defects for multistage semiconductor fabrication based on applied association rule mining”, 2018 INFORMS Annual Meeting, Nov 2018, Phoenix, AZ, USA.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Active inspection for cost-effective fault prediction in manufacturing process", 2019 Fall Conference of Korean Institute of Industrial Engineers (KIIE), Nov 2019, Seoul, Korea.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Active learning of convolutional neural networks for cost-effective wafer map pattern classification", 2019 Spring Conference of Korean Institute of Industrial Engineers (KIIE), Apr 2019, Gwangju, Korea.
◾ Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho, “Identifying the cause of product defects using after-sales service data”, 2015 Fall Conference of Korea Data Mining Society (KDMS), Nov 2015.
◾ Jaewoong Shim, Sungzoon Cho, “Expanding Minority Area: Oversampling method in imbalanced data classification”, 2015 Spring Conference of Korea Business Intelligence Data Mining Society (KDMS), April 2015.
◾ Jaewoong Shim, Eunji Kim, Seokho Kang, Sungzoon Cho, "Hybrid approach with centroid based classification and SVM for multi-class text classification", 2014 Fall Conference of Korea Business Intelligence Data Mining Society (KDMS), Nov 2014.
◾ Jaewoong Shim, Seokho Kang, Sungzoon Cho, "Improving the accuracy of rotation forest using kernel PCA", 2014 Spring Joint Conference of Korean Institute of Industrial Engineers (KIIE), May 2014.
◾ 박정원, 최봉준, 양정열, 강형석, 심재웅, 노이즈 레이블 환경에서 대조학습을 이용한 SSD 고장예측, 한국데이터마이닝학회 2023 추계 학술대회, 서울 , 2023심재웅
◾ 배소희, 이성호, 심재웅, 초기 데이터 부족으로 발생하는 Coldstart 문제 해결을 위한 CLIP 기반 Active Learning, 한국데이터마이닝학회 2023 추계 학술대회, 서울 , 2023심재웅
◾ 배소희, 김지원, 심재웅, 지도학습 기반 불량 탐지 모델을 위한 능동학습 초기화 방법론, 대한산업공학회 2023 추계 학술대회, 울산, 2023심재웅
◾ 허준봉, 손민혁, 심재웅, Knowledge Distillation for cost effective fault prediction in manufacturing process, 대한산업공학회 2023 추계 학술대회, 울산 , 2023심재웅
◾ 이성호,심재웅, 환경 변화에 강건한 불량 탐지 모델 구축을 위한 도메인 일반화 프레임워크, 대한산업공학회/한국경영과학회 2023 춘계 공동학술대회, 제주, 2023심재웅
◾ 이성호, 심재웅, Robust Target Tracking using TDOA Probabilistic Image, SAS 논문 경진대회, 부경대학교 대연캠퍼스, 2022심재웅
Projects
◾ Nov 2019 ~ Jul 2020, Data-driven Diagnosis and Fault Prediction using Machine Learning, Samsung Electronics
◾ Oct 2019 ~ Apr 2020, The Development of Intelligent Diagnostic Technology to Enhance Quality of Convertor, Hyundai Motor
◾ Nov 2018 ~ May 2019, Data Analysis of Driving Pattern for Advanced Driver Assistance System, Hyundai Motor
◾ Apr 2015 ~ Aug 2015, Data Mining Process for Quality Management of Home Appliances, Samsung Electronics
◾ Jul 2014 ~ Jun 2015, Data Mining-based Intelligent Process Control System for Semiconductor Manufacturing, Samsung Electronics
◾ Jan 2014 ~ Jun 2014, Data Analysis to Understanding Students in College for Efficient Academic Management, Office of Information System & Technology, Seoul National University
◾ Oct 2019 ~ Apr 2020, The Development of Intelligent Diagnostic Technology to Enhance Quality of Convertor, Hyundai Motor
◾ Nov 2018 ~ May 2019, Data Analysis of Driving Pattern for Advanced Driver Assistance System, Hyundai Motor
◾ Apr 2015 ~ Aug 2015, Data Mining Process for Quality Management of Home Appliances, Samsung Electronics
◾ Jul 2014 ~ Jun 2015, Data Mining-based Intelligent Process Control System for Semiconductor Manufacturing, Samsung Electronics
◾ Jan 2014 ~ Jun 2014, Data Analysis to Understanding Students in College for Efficient Academic Management, Office of Information System & Technology, Seoul National University