Machine Learning, Artificial Intelligence, Industry 4.0 manufacturing systems, Data Analytics, Design Engineering, Biomedical Engineering.
Dr. Jaskaran Singh is an active researcher in the area of machine learning, deep learning, cyber-physical systems, Industry 4.0 manufacturing systems. Dr. Singh has worked in the area of predictive maintenance of industrial rotating machinery components during his Ph.D. from IIT Delhi, India. He further extended his research area to Industrial big data analytics, Industry 4.0 manufacturing systems, and artificial intelligence during his tenure as a Postdoctoral Fellow at the University of Cincinnati, USA. He has a wide experience of developing and deploying AI-enabled prognostic and health management solutions for industrial machinery. Dr. Singh is involved in many national and international collaborations and published numerous journals and international conference publications.
- PhD in Mechanical Engineering, IIT Delhi
- MTech Design Engineering, IIT Delhi
- B.E. in Mechanical Engineering, Thapar University
Teaching and Work Experience
- Assistant Professor, Thapar Institute of Engineering & Technology, Patiala, India
- Post-Doctoral Fellow, Center for Intelligent Maintenance Systems (IMS Center), University of Cincinnati, USA
- Adjunct Assistant Professor, Department of Mechanical and Materials Engineering, University of Cincinnati, USA
- July 2019 – November 2019
- Research Assistant, IIT Delhi (funded project from Indian Space Research Organisation (ISRO), India)
- Predictive Analytics/Data Analytics
- Artificial Intelligence
- Industry 4.0 manufacturing systems
- Preventive Maintenance/ Condition Monitoring
- Biomedical Engineering
Publications and other Research Outputs
SCI 11, Non-SCI 06, Conference Papers 05
Journal Papers: SCI/SCIE
- Elisa Negri, Vibhor Pandhare, Laura Cattaneo, Jaskaran Singh, Marco Macchi and Jay Lee, 2021. Field-synchronized Digital Twin framework for production scheduling with uncertainty. Journal of Intelligent Manufacturing, 32(4), pp.1207-1228.
- Moslem Azamfar, Jaskaran Singh, Xiang Li, and Jay Lee, 2021. Cross-domain gearbox diagnostics under variable working conditions with deep convolutional transfer learning. Journal of Vibration and Control, 27(7-8), pp.854-864.
- Moslem Azamfar, Jaskaran Singh, Inaki Bravo-Imaz and Jay Lee, 2020. Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis. Mechanical Systems and Signal Processing, 144, p.106861.
- Jay Lee, Jun Ni, Jaskaran Singh, Baoyang Jiang, Moslem Azamfar, and Jianshe Feng, 2020. Intelligent Maintenance Systems and Predictive Manufacturing. Journal of Manufacturing Science and Engineering, 142(11), p.110805
- Jaskaran Singh, Ashish K Darpe, and Satinder Paul Singh, 2020. Bearing remaining useful life estimation using an adaptive data-driven model based on health state change point identification and K-means clustering. Measurement Science and Technology, 31(8), p.085601.
- Jaskaran Singh, Moslem Azamfar, Fei Li. and Jay Lee, 2020. A systematic review of machine learning algorithms for PHM of rolling element bearings: fundamentals, concepts, and applications. Measurement Science and Technology, 32(1), p.012001.
- Jaskaran Singh, Moslem Azamfar, Abhijeet Ainapure, and Jay Lee, 2020. Deep learning-based cross-domain adaptation for gearbox fault diagnosis under variable speed conditions. Measurement Science and Technology, 31(5), p.055601.
- Yubin Pan, Rongjing Hong, Jie Chen, Jaskaran Singh, Xiaodong Jia, Performance degradation assessment of a wind turbine gearbox based on multi-sensor data fusion. Mechanism and Machine Theory, 137, 2019, pp.509-526.
- Jaskaran Singh, Ashish K Darpe and Satinder Paul Singh, Rolling element bearing fault diagnosis based on over-complete rational dilation wavelet transform and auto-correlation of analytic energy operator. Mechanical Systems and Signal Processing, 100, 2018, pp.662-693.
- Jaskaran Singh, Ashish K Darpe and Satinder Paul Singh, Bearing damage assessment using Jensen-Rényi Divergence based on EEMD. Mechanical Systems and Signal Processing, 87, 2017, pp.307-339.
- Jaskaran Singh and B P Patel, Ratcheting analysis of joined conical cylindrical shells. Structural Engineering and Mechanics, 55(5), 2015, pp.913-929.
Journal Publications: Non-SCI
- Jay Lee., Jaskaran Singh, Moslem Azamfar and Vibhor Pandhare, V., 2020. Industrial AI and predictive analytics for smart manufacturing systems. In Smart Manufacturing (pp. 213-244). Elsevier.
- Jay Lee., Jaskaran Singh, Moslem Azamfar and Keyi Sun., 2020. Industrial AI: A Systematic Framework for AI in Industrial Applications. China Mechanical Engineering, 31(01), p.37.
- Jay Lee, Moslem Azamfar, Jaskaran Singh and Siahpour, S., 2020. Integration of digital twin and deep learning in cyber‐physical systems: towards smart manufacturing. IET Collaborative Intelligent Manufacturing, 2(1), pp.34-36.
- Jay Lee, Moslem Azamfar and Jaskaran Singh, A Blockchain Enabled Cyber-Physical System Architecture for Industry 4.0 Manufacturing Systems. Manufacturing letters, 20, 2019, pp.34-39.
- Jay Lee, Hossein Davari, Jaskaran Singh and Vibhor Pandhare, Industrial Artificial Intelligence for industry 4.0-based manufacturing systems. Manufacturing letters, 18, 2018, pp.20-23.
- Moslem Azamfar, Xiaodong Jia, Vibhor Pandhare, Jaskaran Singh, Hossein Davari and Jay Lee, 2019. Detection and diagnosis of bottle capping failures based on motor current signature analysis. 47th SME North American Manufacturing Research Conference, NAMRC 47, Pennsylvania, USA Procedia Manufacturing, 34, pp.840-846.
- Vibhor Pandhare, Jaskaran Singh and Jay Lee, 2019, May. Convolutional Neural Network Based Rolling-Element Bearing Fault Diagnosis for Naturally Occurring and Progressing Defects Using Time-Frequency Domain Features. In 2019 Prognostics and System Health Management Conference (PHM-Paris) (pp. 320-326). IEEE.
- Elisa Negri, Hossein Davari, Laura Cattaneo, Jaskaran Singh, Marco Macchi, and Jay Lee, A Digital Twin-based scheduling framework including Equipment Health Index and Genetic Algorithms. 13th IFAC Workshop on Intelligent Manufacturing Systems Oshawa, Ontario, Canada, 12-14 August 2019.
- Qibo Yang, Jaskaran Singh, and Jay Lee, 2019. Isolation-based feature Selection for Unsupervised Outlier Detection. In Proceedings of the Annual Conference of the PHM Society (Vol. 11, No. 1).
- Jaskaran Singh, Ashish K Darpe and Satinder Paul Singh, 2015. Bearing Degradation assessment using EMD and Jensen-Rényi divergence-based features. 17th ISME Conference on Advances in Mechanical Engineering, Indian Institute of Technology Delhi, October 3 - October 4, 2015
Ongoing Research Collaborations
Name of Collaborative Agency
Center for Intelligent Maintenance Systems (IMS Center), University of Cincinnati, USA
Predictive Maintenance of industrial machinery
Dr. Jay Lee
University of Cincinnati, USA
- Four SCI Journal Publication
- One Elsevier book chapter
All India Institute of Medical Sciences
Dr. Asit Ranjan Mridha
AIIMS, New Delhi
Courses of Interest
- Machine Design
- Computer Aided Design and Analysis
- Mechanics of Machines
- Dynamics and Vibrations
- Mechanical Vibrations
- Engineering Drawing
PhD Thesis Guided
ME Thesis Guided
- Expert lecture on “Industrial AI: A Systematic Approach” in the 36th IMS Center IAB and Industrial AI Virtual Workshop on March 19th, 2021 organized by Center. for Intelligent Maintenance Systems, University of Cincinnati (USA).
- Expert lecture in short-term training program titled ‘Elements of Smart Manufacturing (ESM)’ scheduled from February 15th -20th, 2021, at Indian Institute of Technology Madras, Chennai. The talks were delivered on the topics of “Smart factories" and “Data analytics (Case studies of Industry 4.0 solution implementation)” on February 15, 2021
- Expert lecture on “Advances and Trends of Industry 4.0 in Industrial Big Data Environment” in a TEQIP-III sponsored Online Faculty Development Program on “Mechanical Vibrations, Rotor dynamics and Signal processing” from 13th to 17th July 2020 organized by Darbhanga College of Engineering (DCE), Darbhanga.
- Measurement Science and Technology
- IET Electric Power Applications
- Capstone Mentor for UG final year (2020-2021)
- Member, Curriculum Review Committee of UG (2020-2021)
- Member, ABET accreditation team (2021)
- Member, NBA accreditation team (2020)
- Member, Ph.D. Entrance Exam Committee (2019-2021)
Awards and Honours
- India Ministry of Human Resource & Development Doctoral fellowship, IIT Delhi (2016-2018)
- Indian Ministry of Human Resources & Development GATE scholarship, IIT Delhi (2011-2013)
- Achieved all India rank 269 (99.6 percentile) in GATE – 2011.