Xiaodong Jia

Ph.D: University of Cincinnati Cincinnati, US, 2018 (MECH: Industrial Big Data, Prognostic and Health Management)

M.S.: Shanghai Jiaotong University Shanghai, China, 2014 (MECH: Turbomachinery)

B.S.: Central South University Changsha, China, 2008 (MECH)

Lab Website: 
https://www.intelligentmetrology.com/

- Smart Manufacturing and Maintenance
- Advanced Process Control (APC)
- Machine Learning and Data Mining
- Data-driven Modeling and Intelligent Systems
- Prognostics and Health Management (PHM)

07-2008 -01-2011 Project/Quality Management, Siemens, Shanghai, China

01-2019 -12-2019 Post-Doc Research Fellow, Center for Intelligent Maintenance Systems, ME Department, University of Cincinnati, Cincinnati, US

05-2017 -08-2017 Summer Intern, General Motors, Warren, MI, US

01-2020 -08-2022 Research Assistant Professor, University of Cincinnati, Cincinnati

08-2022 -To Present Assistant Professor (ISE-Data Science Focus), University of Cincinnati, Cincinnati

Investigators:Jia, Xiaodong 01-01-2024 -12-31-2024 Applied Materials, Inc. Transfer Learning and Data Anonymization with Knowledge Retention Role:PI 48960.00 Hold Level:Industry

Grant: #2023-09 / W15QKN-19-3-0003 Investigators:Jia, Xiaodong 09-01-2023 -04-30-2025 Department of the Army Closed-Loop Product Defect Identification and Remediation for Semi-Continuous Roll-to-Part Manufacturing Systems Role:PI 498235.72 Hold Level:Federal

Grant: #132988-Z7682201 Investigators:Jia, Xiaodong 09-01-2023 -08-31-2024 National Institute of Standards and Technology Digital Twin - Enabled Yield Enhancement Methodology for Semiconductor Manufacturing by Using Stream-of-Quality Analytics Role:PI 32497.00 Hold Level:Federal

01-01-2023 -12-31-2023 Applied Materials, Inc. Transfer Learning and Data Anonymization with Knowledge Retention Phase 2 Role:PI 46841.00 Hold Level:Industry

01-01-2023 -12-31-2023 Applied Materials, Inc. Transfer Learning and Data Anonymization with Knowledge Retention Phase 2 Role:PI 46841.00 Hold Level:Industry

12-19-2022 -12-31-2028 General Motors Corporation GM Master Agreement Role:PI 0.00 Hold Level:Industry

12-19-2022 -12-31-2028 General Motors Corporation GM Master Agreement Role:PI 0.00 Hold Level:Industry

Investigators:Jia, Xiaodong; Lee, Jay 11-01-2022 -03-31-2023 Hitachi High-Technologies Corporation Hitachi High-Technologies Corp - 2022-2 (Extension of award 014612-00001) Role:Collaborator 39834.00 Hold Level:Industry

Investigators:Jia, Xiaodong; Lee, Jay 10-01-2022 -09-30-2023 General Motors Corporation Fleet-Sourced Electric Vehicle Battery Life Model Adaptation Role:PI 98409.00 Hold Level:Industry

Grant: #EAA/W15QKN-19-3-0003 Investigators:Jia, Xiaodong; Lee, Jay 10-01-2022 -06-30-2023 The Digital Manufacturing Institute Predictive Maintenance for Multi-Stage Roll-to-Roll Manufacturing Role:Collaborator 482770.00 Hold Level:Industry

Grant: #70NANB22H092 Investigators:Jia, Xiaodong; Kim, Jay; Shi, Jing 08-15-2022 -02-14-2024 National Institute of Standards and Technology Industrial Artificial Intelligence Consortium to Advance High Mix Production Role:Collaborator 298106.00 Awarded Level:Federal

Investigators:Jia, Xiaodong; Lee, Jay 07-01-2022 -03-31-2023 Mitsubishi Electric Corporation MELCO 2022 Role:Collaborator 90492.00 Hold Level:Industry

Grant: #IMS Center Membership Investigators:Jia, Xiaodong 07-01-2022 -06-30-2023 United Microelectronics Corporation IMS Center Membership Agreement for United Microelectronics Corporation (UMC).SIGNATURE ONLY NEEDED - no proposal submission Role:PI 0.00 Hold Level:Industry

Investigators:Jia, Xiaodong; Lee, Jay 06-01-2022 -09-30-2022 Hitachi High-Technologies Corporation Amendment (extension) of Award 014078-00002 - Digital Twin based Plasma Etching Chamber Matching and Machine Calibration Considering Sensor Drift Role:Collaborator 39620.00 Hold Level:Industry

Investigators:Jia, Xiaodong; Lee, Jay 02-01-2022 -05-31-2022 United Microelectronics Corporation UMC - Applications of Machine Learning Operation Techniques Role:Collaborator 49128.00 Hold Level:Industry

Investigators:Jia, Xiaodong; Lee, Jay 01-01-2022 -10-31-2022 Applied Materials, Inc. Applied Materials 2022 - Transfer Learning and Data Anonymization with Knowledge Retention Role:Collaborator 46489.00 Hold Level:Industry

Investigators:Jia, Xiaodong 11-01-2021 -03-31-2022 Hitachi High-Technologies Corporation Phase 2021-2: Digital Twin based Plasma Etching Chamber Matching and Machine Calibration Considering Sensor Drift Role:PI 40792.00 Hold Level:Industry

Grant: #60NANB21D114 Investigators:Jia, Xiaodong 10-01-2021 -09-30-2023 National Institute of Standards and Technology Robust ball screw prognosis based on a physics informed model for online preload estimation Role:PI 109967.00 Hold Level:Federal

Grant: #Full Mbrship Agreement-UMC Investigators:Jia, Xiaodong 09-23-2021 -09-22-2022 United Microelectronics Corporation IMS Center Membership Agreement for United Microelectronics Corporation (UMC). Role:PI 40000.00 Hold Level:Industry

Grant: #Full Mbrship Agreement-TSMC Investigators:Jia, Xiaodong 09-23-2021 -09-22-2022 Taiwan Semiconductor Manufacturing Company Ltd. IMS Center Membership for Taiwan Semiconductor Manufacturing Corporation (TSMC) Role:PI 40000.00 Hold Level:Industry

Grant: #Full Mbrship Agreement-Kennametal 09-14-2021 -09-13-2022 Kennametal Inc. IMS Center Membership for Kennametal Role:PI 40000.00 Hold Level:Industry

07-01-2021 -03-31-2022 Mitsubishi Electric Corporation Health Assessment & Fault Detection for Industrial Robots Role:PI 88332.00 Hold Level:Industry

Grant: #2021 Industry Sponsored Research Agreement Investigators:Jia, Xiaodong 04-01-2021 -09-30-2021 Power Solutions International Power Solutions International Inc. (Phase I) Role:PI 61051.00 Hold Level:Industry

04-01-2021 -09-30-2021 Hitachi High-Technologies Corporation Phase 2021-1: Development of digital twin model for Hitachi plasma etching tool and calibration of tool performance shift Role:PI 0.00 Hold Level:Industry

Grant: #JDA-358 Investigators:Jia, Xiaodong 01-01-2021 -10-31-2021 Applied Materials, Inc. Multivariate Simulation Dataset Generation for Fault Detection with Semi-Automated Feature Extraction and Semi-supervised Limits Setting Applied to Semiconductor Manufacturing Processes Role:PI $37,942.00 Awarded Level:Industry

Grant: #2020 Industry Sponsored Research Agreement Investigators:Jia, Xiaodong 11-01-2020 -03-31-2021 Hitachi High-Technologies Corporation Phase V: Chamber Matching based on Etching Digital Twin Model Role:PI $51,867.00 Awarded Level:Foreign Industry

Grant: #2020 Industry Agreement Investigators:Jia, Xiaodong 11-01-2020 -04-30-2021 United Microelectronics Corporation Applications of Machine Learning Operation Techniques Role:PI 49665.00 Hold Level:Industry

Grant: #2020 Training Agreement Investigators:Jia, Xiaodong 08-01-2020 -10-31-2020 Taiwan Semiconductor Manufacturing Company Ltd. TSMC Training Role:PI $26,324.00 Awarded Level:Foreign Industry

Grant: #2020 Teaming Agreement Investigators:Jia, Xiaodong 08-01-2020 -10-31-2020 Taiwan Semiconductor Manufacturing Company Ltd. TSMC Training Role:PI 0.00 Active Level:Industry

Grant: #2020 Industry Sponsored Research Agreement Investigators:Jia, Xiaodong 05-01-2020 -12-31-2021 Winbond Electronics Corporation Winbond Electrostatic (ESC) Chuck Remaining Useful Life Role:PI $99,280.00 Active Level:Foreign Industry

Grant: #2020 Industry Sponsored Program Agreement Investigators:Jia, Xiaodong 04-01-2020 -12-31-2020 Mitsubishi Electric Corporation Mitsubishi Electric Research 2020 Role:PI $91,801.00 Awarded Level:Industry

Grant: #2020 Industry Sponsored Research Agreement Investigators:Jia, Xiaodong 04-01-2020 -09-30-2020 Hitachi High-Technologies Corporation Phase IV Recipe Optimization Based on Process Sensor Variable Profiles and Etch Rate Role:PI $54,578.00 Awarded Level:Foreign Industry

Grant: #2020 Industry Sponsored Research Agreement Investigators:Jia, Xiaodong; Kim, J. 03-01-2020 -05-31-2020 AU Optronics Corporation PHM Methods for Robot Arms and Pumps Role:Collaborator $31,619.00 Active Level:Foreign Industry

Peer Reviewed Publications

Dai, Honghao; Jia, Xiaodong; Pahren, Laura; Lee, Jay; Foreman, Brandon (2020. ) Intracranial Pressure Monitoring Signals After Traumatic Brain Injury: A Narrative Overview and Conceptual Data Science Framework.Frontiers in neurology, , 11 ,959 More Information

Jia, X.; Jin, C.; Buzza, M.; Wang, W.; Lee, J. (2016. ) Wind turbine performance degradation assessment based on a novel similarity metric for machine performance curves .Renewable Energy, , 99 (7 ) ,1191-1201

Cai, Haoshu; Jia, Xiaodong; Feng, Jianshe; Li, Wenzhe; Pahren, Laura; Lee, Jay (2020. ) A similarity based methodology for machine prognostics by using kernel two sample test.ISA transactions, , 103 ,112-121 More Information

Jia, X.; Zhao, M.; Buzza, M.; Di, Y.; Lee, J. (2017. ) A geometrical investigation on the generalized lp/lq norm for blind deconvolution .Signal Processing, , 134 (7 ) ,63-69

Zhao, M.; Jia, X. (2017. ) A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery .Mechanical Systems and Signal Processing, , 94 (7 ) ,129-147

Jia, X.; Zhao, M.; Di, Y.; Jin, C.; Lee, J. (2017. ) Investigation on the kurtosis filter and the derivation of convolutional sparse filter for impulsive signature enhancement .Journal of Sound and Vibration, , 386 (7 ) ,433-448

Jia, X.; Jin, C.; Buzza, M.; Di, Y.; Siegel, D.; Lee, J. (2018. ) A deviation based assessment methodology for multiple machine health patterns classification and fault detection .Mechanical Systems and Signal Processing, , 99 (7 ) ,244-261

Jia, X.; Di, Y.; Feng, J.; Yang, Q.; Dai, H.; Lee, J. (2018. ) Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks .Journal of Process Control, , 62 (7 ) ,44-54

Jia, X.; Zhao, M.; Di, Y.; Yang, Q.; Lee, J. (2018. ) Assessment of Data Suitability for Machine Prognosis Using Maximum Mean Discrepancy .IEEE Transactions on Industrial Electronics, , 65 (7 ) ,5872-5881

Zhao, M.; Jia, X.; Lin, J.; Lei, Y.; Lee, J. (2018. ) Instantaneous speed jitter detection via encoder signal and its application for the diagnosis of planetary gearbox .Mechanical Systems and Signal Processing, , 98 (4 ) ,16-31

Li, P.; Jia, X.; Feng, J.; Davari, H.; Qiao, G.; Hwang, Y.; Lee, J. (2018. ) Prognosability study of ball screw degradation using systematic methodology .Mechanical Systems and Signal Processing, , 109 (4 ) ,45-57

Jia, X.; Huang, B.; Feng, J.; Cai, H.; Lee, J. (2018. ) Review of PHM data competitions from 2008 to 2017: Methodologies and analytics .Mechanical Systems and Signal Processing, , 99 (7 ) ,244-261

Jia, X.; Zhao, M.; Di, Y.; Li, P.; Lee, J. (2018. ) Sparse filtering with the generalized lp/lq norm and its applications to the condition monitoring of rotating machinery .Mechanical Systems and Signal Processing, , 102 (7 ) ,198-213

Cai, H.; Jia, X.; Feng, J.; Yang, Q.; Hsu, Y. M.; Chen, Y.; Lee, J. (2019. ) A combined filtering strategy for short term and long term wind speed prediction with improved accuracy .Renewable Energy, , 136 (4 ) ,1082-1090

Jia, X.; Duan, S.; Lee, C.; Radecki, P.; Lee, J. (2019. ) A methodology for the early diagnosis of vehicle torque converter clutch degradation .IEEE transactions on semiconductor manufacturing, , 2019-August (2 ) ,529-534

Li, P.; Jia, X.; Sumiya, M.; Kamaji, Y.; Ishiguro, M.; Pahren, L.; Lee, J. (2019. ) A novel method for deposit accumulation assessment in dry etching chamber .IEEE transactions on semiconductor manufacturing, , 32 (2 ) ,183-189

Jia, X.; Cai, H.; Hsu, Y.; Li, W.; Feng, J.; Lee, J. (2019. ) A novel similarity-based method for remaining useful life prediction using kernel two sample test .IEEE transactions on semiconductor manufacturing, , 11 (2 ) ,529-534

Feng, J.; Jia, X.; Zhu, F.; Yang, Q.; Pan, Y.; Lee, J. (2019. ) An intelligent system for offshore wind farm maintenance scheduling optimization considering turbine production loss .Journal of Intelligent and Fuzzy Systems, , 37 (5 ) ,6911-6923

Feng, J.; Jia, X.; Zhu, F.; Moyne, J.; Iskandar, J.; Lee, J. (2019. ) An online virtual metrology model with sample selection for the tracking of dynamic manufacturing processes with slow drift .IEEE transactions on semiconductor manufacturing, , 32 (4 ) ,574-582

Azamfar, M.; Jia, X.; Pandhare, V.; Singh, J.; Davari, H.; Lee, J. (2019. ) Detection and diagnosis of bottle capping failures based on motor current signature analysis .Procedia Manufacturing, , 34 (4 ) ,840-846

Pan, Y.; Hong, R.; Chen, J.; Singh, J.; Jia, X. (2019. ) Performance degradation assessment of a wind turbine gearbox based on multi-sensor data fusion .Mechanism and Machine Theory, , 137 ,509-526

Li, P.; Jia, X.; Feng, J.; Zhu, F.; Miller, M.; Chen, L. Y.; Lee, J. (2020. ) A novel scalable method for machine degradation assessment using deep convolutional neural network .Measurement: Journal of the International Measurement Confederation, , 151 ,235-247

Cai, H.; Jia, X.; Feng, J.; Li, W.; Pahren, L.; Lee, J. (2020. ) A similarity based methodology for machine prognostics by using kernel two sample test .Isa Transactions, , 103 ,112-121

Cai, H.; Jia, X.; Feng, J.; Li, W.; Hsu, Y. M.; Lee, J. (2020. ) Gaussian Process Regression for numerical wind speed prediction enhancement .Renewable Energy, , 146 ,2112-2123

Li, X.; Jia, X. D.; Zhang, W.; Ma, H.; Luo, Z.; Li, X. (2020. ) Intelligent cross-machine fault diagnosis approach with deep auto-encoder and domain adaptation .Neurocomputing, , 383 ,235-247

Dai, H.; Jia, X.; Pahren, L.; Lee, J.; Foreman, B. (2020. ) Intracranial Pressure Monitoring Signals After Traumatic Brain Injury: A Narrative Overview and Conceptual Data Science Framework .Frontiers in Neurology, , 11 ,235-247

Zhang, W.; Li, X.; Jia, X. D.; Ma, H.; Luo, Z.; Li, X. (2020. ) Machinery fault diagnosis with imbalanced data using deep generative adversarial networks .Measurement: Journal of the International Measurement Confederation, , 152 ,242-253

Li, X.; Jia, X.; Yang, Q.; Lee, J. (2020. ) Quality analysis in metal additive manufacturing with deep learning .Journal of Intelligent Manufacturing, , 383 ,235-247

Li, W.; Jia, X.; Li, X.; Wang, Y.; Lee, J. (2021. ) A Markov model for short term wind speed prediction by integrating the wind acceleration information .Renewable Energy, , 164 ,242-253

Cai H.; Jia X.; Feng J.; Yang Q.; Li W.; Li F.; Lee J. (11-01-2021. ) A unified Bayesian filtering framework for multi-horizon wind speed prediction with improved accurac.Renewable Energy, , 178 ,709-719 More Information

Wang C.; Dani J.; Li X.; Jia X.; Wang B. (04-26-2021. ) Adaptive Fingerprinting: Website Fingerprinting over Few Encrypted Traffic.CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy, , 149-160 More Information

Zhu F.; Jia X.; Miller M.; Li X.; Li F.; Wang Y.; Lee J. (02-01-2021. ) Methodology for Important Sensor Screening for Fault Detection and Classification in Semiconductor M.IEEE Transactions on Semiconductor Manufacturing, , 34 (1 ) ,65-73 More Information

Pandhare V.; Li X.; Miller M.; Jia X.; Lee J. (01-01-2021. ) Intelligent Diagnostics for Ball Screw Fault through Indirect Sensing Using Deep Domain Adaptation.IEEE Transactions on Instrumentation and Measurement, , 70 , More Information

Jia X.; Li W.; Wang W.; Li X.; Lee J. (11-03-2020. ) Development of multivariate failure threshold with quantifiable operation risks in machine prognosti.Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM, , 12 (1 ) , More Information

Li X.; Jia X.; Wang Y.; Yang S.; Zhao H.; Lee J. (10-01-2020. ) Industrial Remaining Useful Life Prediction by Partial Observation Using Deep Learning with Supervis.IEEE/ASME Transactions on Mechatronics, , 25 (5 ) ,2241-2251 More Information

Peres R.S.; Jia X.; Lee J.; Sun K.; Colombo A.W.; Barata J. (01-01-2020. ) Industrial Artificial Intelligence in Industry 4.0 -Systematic Review, Challenges and Outlook.IEEE Access, , More Information

Wang Y.; Jia X.; Li X.; Yang S.; Zhao H.; Lee J. (01-01-2020. ) A machine vision based monitoring system for the LCD panel cutting wheel degradation.48 ,49-53 More Information

Yang S.; Li X.; Jia X.; Wang Y.; Zhao H.; Lee J. (01-01-2020. ) Deep learning-based intelligent defect detection of cutting wheels with industrial images in manufac.48 ,902-907 More Information

Hsu Y.M.; Jia X.; Li W.; Manganaris P.; Lee J. (05-01-2022. ) Sequential optimization of the injection molding gate locations using parallel efficient global opti.International Journal of Advanced Manufacturing Technology, , 120 (5-6 ) ,3805-3819 More Information

Lee J.; Siahpour S.; Jia X.; Brown P. (04-01-2022. ) Introduction to resilient manufacturing systems.Manufacturing Letters, , 32 ,24-27 More Information

Lu C.; Jia X.; Lee J.; Shi J. (01-01-2022. ) Knowledge transfer using Bayesian learning for predicting the process-property relationship of Incon.Virtual and Physical Prototyping, , 17 (4 ) ,787-805 More Information

Li W.; Jia X.; Hsu Y.M.; Liao C.H.; Wang Y.; Lin M.T.; Lee J. (01-01-2022. ) A Novel Methodology for Lens Matching in Compact Lens Module Assembly.IEEE Transactions on Automation Science and Engineering, , More Information

Feng J.; Jia X.; Cai H.; Zhu F.; Li X.; Lee J. (09-01-2021. ) Cross Trajectory Gaussian Process Regression Model for Battery Health Prediction.Journal of Modern Power Systems and Clean Energy, , 9 (5 ) ,1217-1226 More Information

Yang Q.; Jia X.; Li X.; Feng J.; Li W.; Lee J. (06-01-2021. ) Evaluating Feature Selection and Anomaly Detection Methods of Hard Drive Failure Prediction.IEEE Transactions on Reliability, , 70 (2 ) ,749-760 More Information

Lee J.; Sun K.; Jia X.; Li X.; Yang Q. (01-01-2021. ) Collaborative platform for remote manufacturing systems using industrial internet and digital twin i.Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, , 2 , More Information

Di Y.; Jia X.; Lee J. (06-01-2017. ) Enhanced virtual metrology on chemical mechanical planarization process using an integrated model an.International Journal of Prognostics and Health Management, , 8 (2 ) , More Information

1st Place in the 1st Foxconn industrial AI Data Challenge 2020

3rd Place in Aramis Challenge 2020: Prognostics and Health Management in Evolving Environments

1st Place in the PHM Data Challenge 2016, Hosted by the PHM society

 For prospective PhD candidates interested in joining my lab, please note the following:
 

1. We encourage students with degrees in Mechanical Engineering (ME), Aerospace Engineering (AE), or Electrical Engineering (EE) who are interested in learning data science to apply.
2. Candidates with experience in areas such as manufacturing processes and systems, robotics, sensing and monitoring, and industrial electronics are strongly encouraged to apply.
3. Proficient matlab and python programming skills are extremely important for successful PhD study. Prior experience with AI and ML are optional.
4. Applicants with backgrounds in Industrial Engineering (IE), Applied Mathematics, Computer Science (CS), or Biomedical Engineering (BME) please check if you attended these fundamental engineering courses, including Mechanics, Control Theory, Manufacturing Technology, Vibration Analysis, Signal Processing, etc. Please email before applying.
5. Interested applicants please read our recent research here: https://www.intelligentmetrology.com/