Referred Journals and Transactions

* corresponding author（“*”为通讯作者）; _graduate student supervised（"_"为研究生）

  1. Ji Song, Xing Wang, Jianguo Wu, Xiaowei Yue*, 2024, "High Dimensional Data Decomposition for Anomaly Detection of Textured Images" , submitted
  2. Yongxiang Li, Yu Tian, Qian Xiao*, Jianguo Wu, 2024, "Penalized Additive Gaussian Process for Screening and Optimization of Quantitative and Qualitative Factors in Black-Box Systems", submitted (Best General Paper Competition Finalist, 2024 INFORMS Annual Meeting, Data Mining Society )
  3. Zheren Song, Jianguo Wu*, Yongxiang Li, Xiaowei Yue, Xiaochun Li, 2024, "DiffPore: deep generative learning enables defect morphology prediction in metal additive manufacturing", submitted
  4. Jinwei Yao, Chao Wang*, Jianguo Wu, Yongxiang Li, 2024, “Transfer Learning of Stochastic Kriging for Individualized Prediction”, submitted (Best Student Paper Competition Finalist, 2024 INFORMS Annual Meeting, Quality, Statistics, and Reliability (QSR) Society )
  5. Yongxiang Li, Yunji Zhang, Qian Xiao*, Jianguo Wu, 2024, “A Noise Resistant Control Chart for Detecting Periodicity from Correlation”, submitted
  6. Xinxing Guo, Song Huang, Jianguo Wu*, Chao Wang, 2023, "A Transfer Learning Approach for Remaining Useful Life Prediction subject to Hard Failure Considering Within and Between Population Variations", submitted
  7. Ruiyu Xu, Chao Wang, Yongxiang Li, Jianguo Wu*, 2023, "Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering", second round revew at IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (INFORMS 2023 Data Mining Best Paper Award)
  8. C. Lee, X. Wang, J. Wu, X. Yue*, 2023, "Multi-output Extreme Spatial Model for Complex Production Systems", submitted (Best Paper Award Finalist, 2023 INFORMS Conference on Quality, Statistics, and Reliability)
  9. X. Zhu, J. Son, X. Zhang, J. Wu*,2023, "Solving the distributed integrated process planning and scheduling problem using logic-based Benders decomposition", submitted
  10. Y. Li, H. Zhao, J. Wu*, 2022, "Iterative Hypothesis Testing for Period Estimation of Noisy Signals via Dynamic Significance Levels", submitted
  11. Z. Li, J. Son, Y. Li, J. Wu*, 2022, “Semi-supervised Nonlinear Data Fusion Approach for Health Assessment Considering Prognostic Accuracy”, submitted
  12. Xinming Wang, Yongxiang Li, Xiaowei Yue, Jianguo Wu*, 2024, "Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab Prior", INFORMS Journal on Data Science (Best Paper Award Finalist, INFORMS 2023 Data Mining Best Paper Award Competition)
  13. Y. Kuang, R. Xu, D. Das*, Jianguo Wu*, M. Sir, K. Pasupathy, 2024, "Real-time Monitoring of Markov Chains with Application in Detecting Slowdowns in Hospital Emergency Departments", Flexible Services and Manufacturing Journal, accepted
  14. Ruiyu Xu, Zheren Song, Jianguo Wu*, Chao Wang, Shiyu Zhou, 2024, "Change-point Detection with Deep Learning: A Review", Frontiers of Engineering Management, accepted
  15. Yongxiang Li, Yunji Zhang, Jianguo Wu*, Min Xie, 2024, "Regularized Periodic Gaussian Process for Nonparametric Sparse Feature Extraction from Noisy Periodic Signals", IEEE Transactions on Automation Science and Engineering. accepted
  16. Yongxiang Li, Yunji Zhang, Qian Xiao, Jianguo Wu*, 2023, "Quasi-Periodic Gaussian Process Modeling of Pseudo-Periodic Signals", IEEE Transactions on Signal Processing
  17. Y. Xie, J. Du*, J. Wu, 2023, "Adaptive Particle Filter for Change Point Detection of Profile Data in Manufacturing Systems" , IEEE Transactions on Automation Science and Engineering.
  18. Z. Li, T. Tao, M. Yang, J. Wang, Z. Chen, J. Wu*, 2023, "An Unsupervised Neural Network for Graphical Health
    Index Construction and Residual Life Prediction    ", Engineering Applications of Artificial Intelligence (EAAI)
  19. R. Li, J. Wu, Y. Cheng, Y. Li*, 2023, "PeriodNet: Noise-Robust Fault Diagnosis Method under Varying Speed Conditions", IEEE Transactions on Neural Networks and Learning Systems
  20. Chi Zhang, Jian Cui, Jianguo Wu, Xi Zhang*, 2023, "Attention Mechanism and Texture Contextual Information for Steel Plate Defects Detection", Journal of Intelligent Manufacturing
  21. R. Xu, S. Huang, Z. Song, Y. Gao, J. Wu*, 2023, "A Deep Mixed-effects Modeling Approach for Real-time Monitoring of Metal Additive Manufacturing Process" , IISE Transactions (Best Student Paper Award Finalist, 2022 INFORMS Cluster of Sustainability: Science, Engineering and Analytics, featured by August 2024 issue of ISE Magazine )
  22. Z. Hu, C. Wang, J. Wu, D. Du*, 2023, "Gaussian Process Latent Variable Model-Based Multi-Output Modeling of Incomplete Data" , IEEE Transactions on Automation Science and Engineering
  23. Z. Song, X. Wang, Y. Gao, J. Son, J. Wu*, 2023, "A Hybrid Deep Generative Network for Pore Morphology Prediction in Metal Additive Manufacturing", ASME Transactions, Journal of Manufact. Science and Engineering
  24. X. Zhu, J. Son, X. Zhang, J. Wu*, 2023, "Constraint Programming and Logic-based Benders Decomposition for the Integrated Process Planning and Scheduling Problem" , Omega-International Journal of Management Science
  25. C. Lee, K. Wang, J. Wu, W. Cai, X. Yue*, 2022, "Partitioned Active Learning for Heterogeneous Systems" , ASME Transactions, Journal of Computing and Information Science in Engineering, accepted (2021 INFORMS QSR Best Paper Competition Finalist)
  26. X. Wang, C. Wang*, X. Song, L. Kirby, J. Wu*, 2022, "Regularized Multi-output Gaussian Convolution Process with Domain Adaptation", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), (Best Paper Award in the 2022 INFORMS QSR Best Paper Competition). supplementary material
  27. Y. Gao, X. Wang, J. Son, X. Yue, J. Wu*, 2022, "Hierarchical Modeling of Microstructural Images for Porosity Prediction in Metal Additive Manufacturing via Two-point Correlation Function", IISE Transactions
  28. Z. Li, Y. Li, X. Yue, J. Wu*, E. Zio, 2022, "A Deep Branched Network for Failure Mode Diagnostics and Remaining Useful Life Prediction", IEEE Transactions on Instrumentation & Measurement
  29. C. Lee, X. Wang, J. Wu, X. Yue*, 2022, "Failure-averse Active Learning for Physics-constrained Systems", IEEE Transactions on Automation Science and Engineering (Best Theoretical Paper Award Finalist in the 2022 INFORMS Data Mining and Decision Analytics Workshop)
  30. Y. Gao, X. Huang, Q. Zhou, J. Wu*, 2022, "An Order Statistic Approach for Inference of the Size Distribution of 3D Particle Clusters in Metal Matrix Nanocomposites", CIRP Journal of Manufacturing Science and Technology
  31. Y. Li, Y. Pu, W. Fan, J. Wu, 2022, "Constraint Linear Model for Period Estimation and Sparse Feature Extraction Based on Iterative Likelihood Ratio Test", IEEE Transactions on Industrial Electronics
  32. Y. Wen, X. Guo, J. Son, J. Wu*, 2022, "A Neural Network based Proportional Hazard Model for IoT Signal Fusion and Failure Prediction", IISE Transactions
  33. R. Xu, J. Wu*, X. Yue, Y. Li, 2022, "Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning" , Technometrics (2020 INFORMS QSR Best Student Paper Competition Finalist)
  34. F. Rahman, B. Tseng, Y. Wen, J. Wu*, 2021, "Deep Learning-based Filler Detection and Segmentation in SEM Images for Automated Quality Inspection", Artificial Intelligence for Engineering Design, Analysis and Manufacturing
  35. Y. Gao, X. Huang, C. Wang, J. Wu*, 2021, "Estimating Size and Number Density of Three-dimensional Particles using Truncated Cross-Sectional Data" , ASME Transactions, Journal of Manufact. Science and Engineering
  36. X. Zhu, X. Guo, W. Wang, J. Wu*, 2021, "A Genetic Programming-Based Iterative Approach for The Integrated Process Planning and Scheduling Problem",IEEE Transactions on Automation Science and Engineering
  37. F. Rahman, J. Wu*, B. Tseng, 2021, "Automatic Morphological Extraction of Fibers from SEM Images for Quality Control of Short Fiber-Reinforced Composites Manufacturing", CIRP Journal of Manufacturing Science and Technology
  38. C. Lee, J. Wu, W. Wang, X. Yue*, 2020, "Neural Network Gaussian Process considering Input Uncertainty for Composite Structures Assembly", IEEE/ASME Transactions on Mechatronics (2020 IISE Annual Conference DAIS Best Student Paper Award )
  39. Z. Li, J. Wu*, X. Yue, 2020, "A Shape Constrained Neural Data Fusion Network for Health Index Construction and Remaining Useful Life Prediction", IEEE Transactions on Neural Networks and Learning Systems
  40. Y. Gao, Y. Wen, J. Wu*, 2020, "A Neural Network Based Joint Prognostic Model for Data Fusion and Remaining Useful Life Prediction", IEEE Transactions on Neural Networks and Learning Systems
  41. J. Wu*, H. Xu , J. Feng, B. Tseng, 2020, "Adaptive Minimal Confidence Region Rule for Multivariate Initialization Bias Truncation in Discrete-event Simulations", Technometrics, Supplementary material
  42. C. Zhang, N. Chen, J. Wu* , 2020, "Spatial Rank-based High-dimensional Monitoring Through Random Projection", Journal of Quality Technology
  43. X. Song, M. Shi, J. Wu, W. Sun, 2019, "A New Fuzzy c-means Clustering-based Time Series Segmentation Approach and its Application on Tunnel Boring Machine Analysis", Mechanical Systems and Signal Processing
  44. J. Wu*, H. Xu , C. Zhang, Y. Yuan, 2019, "A Sequential Bayesian Partitioning Approach for Online Steady State Detection of Multivariate System" , IEEE Transactions on Automation Science and Engineering
  45. Y. Wen, J. Wu*, D. Das, B. Tseng, 2018, "Degradation Modeling and RUL Prediction using Wiener Process subject to Multiple Change Points and Unit Heterogeneity", Reliability Engineering and System Safety (Featured by Advances in Engineering)
  46. Y. Wen , J. Wu*, Q. Zhou, B. Tseng, 2018, "Multiple Change-point Modeling and Exact Bayesian Inference of Degradation Signal for Prognostics Improvement", IEEE Transactions on Automation Science and Engineering
  47. N. Chen*, E. Byon, J. Wu , 2016, "A General Wiener Process Model for Heterogeneous Degradations based on Kriging ", Journal of Quality Technology, under revision
  48. J. Wu* , Y. Yuan, H. Gong, B. Tseng, 2018, "Inferring 3D Ellipsoids based on Cross-Sectional Images with Application to Porosity Control of Additive Manufacturing", IISE Transactions (Featured by June issue of the Institute of Industrial and Systems Engineer Magazine)
  49. Y. Wen, J. Wu*, Y. Yuan, 2017, "Multiple Phase Modeling of Degradation Signal for Condition Monitoring and Remaining Useful Life Prediction", IEEE Transactions on Reliability
  50. J. Wu*, Y. Yuan, X. Li, 2017, "Size Distribution Estimation of 3D Particle Clusters in Metal Matrix Nanocomposites Considering Sampling Bias", ASME Transactions, Journal of Manufact. Science and Engineering
  51. J. Wu*, Y. Liu, and S. Zhou, 2016, "Bayesian Hierarchical Linear Modeling of Profile Data with Applications to Quality Control of Nanomanufacturing", IEEE Transactions on Automation Science and Engineering
  52. Y. Hou, J. Wu and Y. Chen*, 2016, "Online Steady State Detection Based on Rao-Blackwellized Sequential Monte Carlo", Quality and Reliability Engineering International
  53. J. Wu, Y. Chen and S. Zhou*, 2016, “On-line Detection of Steady State Operation using a Multiple Change-point Model an Exact Bayesian Inference”, IIE Transactions (2015 ISERC Best Student Paper Award Finalist)
  54. Y. Liu, J. Wu, S. Zhou* and X. Li, 2016, "Microstructure Modeling and Ultrasonic Wave Propagation Simulation of A206-Al2O3 Metal Matrix Nanocomposites for Quality Inspection", ASME Transactions, Journal of Manufact. Science and Engineering.
  55. J. Wu, Y. Chen, S. Zhou* and X. Li, 2015, "On-line Steady State Detection for Process Control Using Multiple Change-point Models and Particle Filters", IEEE Transactions on Automation Science and Engineering
  56. J. Wu, S. Zhou*, and X. Li, 2015, "Ultrasonic Attenuation Based Inspection Method for Scale-up Production of A206-Al2O3 Metal Matrix Nanocomposites", ASME Transactions, Journal of Manufacturing Science and Engineering 137.1,011013
  57. J. Wu, S. Zhou, and X. Li, 2013, "Acoustic Emission Monitoring for Ultrasonic Cavitation Based Dispersion Process", ASME Transactions, Journal of Manufacturing Science and Engineering 135(3), 031015.
  58. Y. Dong, Q. Li, J. Wu, and A. Martini*, 2011, "Friction, Slip and Structural Inhomogeneity of the Buried Interface",Modeling and Simulation in Materials Science and Engineering 19 065003.

Peer Reviewed Conference Paper and Chinese Journals

  1. 蒋建斌，黄松，吴建国*，2024，基于图像分割技术的智能造字研究，北京大学学报（中文核心），已接收
  2. 周云柯，吴建国*，2024，中国碳排放影响因素分析与碳中和路径探寻，中国国土资源经济（中国人文社会科学期刊AMI综合评价核心期刊），已接收
  3. R. Xu, X. Wang, J. Wu*, "Classification Based Hard Disk Drive Failure Prediction: Methodologies, Performance Evaluation and Comparison", 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). IEEE, 2022: 189-195.
  4. Xu, H., Wu, J.*, Tseng, B., "An efficient method for on-line identification of steady state for multivariate systems", Proceedings of the ASME 2018 13th International Manufacturing Science and Engineering Conference
  5. Rahman, F., Wu, J.*, Tseng, B., "Automated Fiber Extraction from SEM images with Application to Quality Control of Fiber-reinforced Composites Manufacturing", Proceedings of the ASME 2018 13th International Manufacturing Science and Engineering Conference
  6. B. Tseng, Z. Hu, J. Wu , A. Renteria, Y. Wen, C. Huang "Scanning Electron Microscopy (SEM) Based Image Data Mining for Quality Control of Nanofiber Reinforced Piezo-Electric Nanocomposites", Proceedings of the 2018 IISE Annual Conference
  7. Wu, J.*, Lin, Y., Tseng, B., "Numerical Simulation of Ultrasonic Wave Propagation in Fiber-enhanced Dielectric Nanocomposites for Quality Inspection ", The Southwest Technology Symposium, 2016
  8. Hu, Z., Tseng, B., Lin, Y., Wu, J.*, "Hough Transform based Automatic Segmentation of Nanofibers from SEM Images", The Southwest Technology Symposium, 2016

Software

  1. Wu, J. and Martini, A.*, 2010, "Atomic Stick-Slip ", DOI: 10254/nanohub-r7771.1, 2009 ( online software used by over 400 researchers)

 

 

 

 

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