Dr. Jay Lee is Clark Distinguished Professor and Director of Industrial AI Center in the Mechanical Engineering Dept. of the Univ. of Maryland College Park. Previously, he served as an Ohio Eminent Scholar, L.W. Scott Alter Chair and Univ. Distinguished Professor at Univ. of Cincinnati. He was Founding Director of National Science Foundation (NSF) Industry/University Cooperative Research Center (I/UCRC) on Intelligent Maintenance Systems ( during 2001-2019 with over 100 company memberships. IMS was selected as the most economically impactful I/UCRC in the NSF Economic Impact Study Report in 2012. He is also the Founding Director of Industrial AI Center ( ). He is a fellow of ASME, SME, PHM Society, and ISEAM, and a member of World Economic Forum (WEF) Global Future Council in Advanced Manufacturing and Value Chain. Previously served as Program Director of NSF during 1991-1998 and Director of United Technologies Research Center during 1998-2000.
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Industrial and Manufacturing Engineering, Engineering, Artificial Intelligence
47517
Scholar Citations
86
Scholar h-index
297
Scholar i10-index
RECENT SCHOLAR PUBLICATIONS
2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing J Lee, H Su, M Macchi, A Polenghi, W Wu, Z Zhao, GQ Huang, K Allgood, ... Machine Learning: Engineering , 2026 2026
Correction to: Case Studies in Digital Transformation A Crespo Márquez, T Seecharan, G Abdul-Nour, J Amadi-Echendu, J Lee Case Studies in Digital Transformation: Integration of Digital Technologies … , 2026 2026
BioPrint-LKM: An evidence-grounded large knowledge model for bioprinting knowledge retrieval and parameter initialization X Huang, H Su, Z Cui, JM Lee, X Gao, R Hu, J Lee, WY Yeong International Journal of Bioprinting , 2026 2026
V-TimesNet: Vision-Augmented TimesNet for Improved Anomaly Detection in Semiconductor Plasma Dry Etching R Wang, D Ji, C Liu, J Lee SSRN , 2025 2025 Citations: 4
Data issues in industrial AI systems: A meta-review and research strategy X Li, Y Cheng, C Møller, J Lee Computers in Industry 173, 104361 , 2025 2025 Citations: 13
UniFault: A Fault Diagnosis Foundation Model from Bearing Data E Eldele, M Ragab, X Qing, Edward, Z Chen, M Wu, X Li, J Lee arXiv:2504.01373 , 2025 2025 Citations: 13
Partial Domain Adaptation for Intelligent Machinery Fault Diagnosis: Leveraging Healthy-Only Target Data for Multi-Class Classification H Su, DY Ji, S Tsuruta, D Arimizu, Y Hachiya, K Wakimoto, J Lee Annual Conference of the PHM Society 17 (1) , 2025 2025 Citations: 1
Agentic AI for smart manufacturing J Lee, H Su Manufacturing Letters , 2025 2025 Citations: 11
Engineering artificial intelligence: framework, challenges, and future direction J Lee, H Su, DY Ji, T Minami Machine Learning: Engineering 1 (1), 013001 , 2025 2025 Citations: 13
Introduction to Industrial Artificial Intelligence DY Ji, H Su, T Minami, J Lee Advances in Artificial Intelligence Applications in Industrial and Systems … , 2025 2025 Citations: 1
Introducing machine learning: engineering J Lee Machine Learning: Engineering, Volume 1, Number 1 1 , 2025 2025
Transfer learning and ensemble learning for fault diagnosis using vibration signals H Su, J Lee 2025 ieee international conference on prognostics and health management … , 2025 2025 Citations: 1
Improving machine calibration performance through systematic feature design in semiconductor manufacturing DY Ji, M Sumiya, Y Kamaji, S Matsukura, W Li, J Lee 2025 36th annual semi advanced semiconductor manufacturing conference (asmc … , 2025 2025 Citations: 1
Rethinking industrial artificial intelligence: A unified foundation framework J Lee, H Su arXiv preprint arXiv:2504.01797 , 2025 2025 Citations: 27
Novel topological machine learning methodology for stream-of-quality modeling in smart manufacturing J Lee, DY Ji, YM Hsu Manufacturing Letters 43, 60-63 , 2025 2025 Citations: 9
Multi-Class Gearbox Fault Diagnosis via Pre-Trained Model-based Domain Adaptation with Healthy-Only Target Data DY Ji, H Su, S Tsuruta, D Arimizu, Y Hachiya, K Wakimoto, J Lee PHM Society Asia-Pacific Conference 5 (1) , 2025 2025 Citations: 1
An advanced diagnostic model for gearbox degradation prediction under various operating conditions and degradation levels H Su, J Lee Annual Conference of the PHM Society 16 (1) , 2024 2024 Citations: 10
A novel technique for multiple failure modes classification based on deep forest algorithm J Taco, P Kundu, J Lee Journal of Intelligent Manufacturing 35 (7), 3115-3129 , 2024 2024 Citations: 9
A unified industrial large knowledge model framework in industry 4.0 and smart manufacturing J Lee, H Su International Journal of AI for Materials and Design 3681, 20 , 2024 2024
PHM for Spacecraft Propulsion Systems: Developing Resilient Models for Real-World Challenges T Minami, DY Ji, J Lee PHM Society European Conference 8 (1), 7-7 , 2024 2024 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
A cyber-physical systems architecture for industry 4.0-based manufacturing systems J Lee, B Bagheri, HA Kao Manufacturing letters 3, 18-23 , 2015 2015 Citations: 8142
Service innovation and smart analytics for industry 4.0 and big data environment J Lee, HA Kao, S Yang Procedia cirp 16, 3-8 , 2014 2014 Citations: 3245
Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications J Lee, F Wu, W Zhao, M Ghaffari, L Liao, D Siegel Mechanical systems and signal processing 42 (1-2), 314-334 , 2014 2014 Citations: 2099
Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics H Qiu, J Lee, J Lin, G Yu Journal of sound and vibration 289 (4-5), 1066-1090 , 2006 2006 Citations: 1870
Recent advances and trends in predictive manufacturing systems in big data environment J Lee, E Lapira, B Bagheri, H Kao Manufacturing letters 1 (1), 38-41 , 2013 2013 Citations: 1786
Industrial Artificial Intelligence for industry 4.0-based manufacturing systems J Lee, H Davari, J Singh, V Pandhare Manufacturing letters 18, 20-23 , 2018 2018 Citations: 1280
Industrial artificial intelligence in industry 4.0-systematic review, challenges and outlook RS Peres, X Jia, J Lee, K Sun, AW Colombo, J Barata IEEE access 8, 220121-220139 , 2020 2020 Citations: 1044
A review on prognostics and health monitoring of Li-ion battery J Zhang, J Lee Journal of power sources 196 (15), 6007-6014 , 2011 2011 Citations: 981
Intelligent prognostics tools and e-maintenance J Lee, J Ni, D Djurdjanovic, H Qiu, H Liao Computers in industry 57 (6), 476-489 , 2006 2006 Citations: 915
Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility SM Rezvanizaniani, Z Liu, Y Chen, J Lee Journal of power sources 256, 110-124 , 2014 2014 Citations: 895
Handbook of maintenance management and engineering M Ben-Daya, SO Duffuaa, A Raouf, J Knezevic, D Ait-Kadi Springer London , 2009 2009 Citations: 732
Industrial big data analytics and cyber-physical systems for future maintenance & service innovation J Lee, HD Ardakani, S Yang, B Bagheri Procedia cirp 38, 3-7 , 2015 2015 Citations: 723
Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods R Huang, L Xi, X Li, CR Liu, H Qiu, J Lee Mechanical systems and signal processing 21 (1), 193-207 , 2007 2007 Citations: 712
A similarity-based prognostics approach for remaining useful life estimation of engineered systems T Wang, J Yu, D Siegel, J Lee 2008 international conference on prognostics and health management, 1-6 , 2008 2008 Citations: 710
Smart agents in industrial cyber–physical systems P Leitao, S Karnouskos, L Ribeiro, J Lee, T Strasser, AW Colombo Proceedings of the IEEE 104 (5), 1086-1101 , 2016 2016 Citations: 623
Cyber-physical systems architecture for self-aware machines in industry 4.0 environment B Bagheri, S Yang, HA Kao, J Lee IFAC-PapersOnLine 48 (3), 1622-1627 , 2015 2015 Citations: 590
Robust performance degradation assessment methods for enhanced rolling element bearing prognostics H Qiu, J Lee, J Lin, G Yu Advanced Engineering Informatics 17 (3-4), 127-140 , 2003 2003 Citations: 558
Maintenance: changing role in life cycle management S Takata, F Kirnura, FJAM van Houten, E Westkamper, M Shpitalni, ... CIRP annals 53 (2), 643-655 , 2004 2004 Citations: 555
Watchdog Agent—an infotronics-based prognostics approach for product performance degradation assessment and prediction D Djurdjanovic, J Lee, J Ni Advanced Engineering Informatics 17 (3-4), 109-125 , 2003 2003 Citations: 472
Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation X Zhou, L Xi, J Lee Reliability engineering & system safety 92 (4), 530-534 , 2007 2007 Citations: 464
