Publications

Journal Publications (* corresponding author, # students advised by me)

See Google Scholar or LAB website for the full publication list

Refereed Journal Papers

J1. Du, J., Zhang, X., and Shi, J., “Pairwise Critical Point Detection Using Torque Signals in Threaded Pipe Connection Processes”, ASME Transactions, Journal of Manufacturing Science and Engineering, vol. 139, no. 9, p. 091002, 2017.

• Best Student Paper Award in Symposium of College of Engineering at Peking University in 2015.

J2. Du, J., Zhang, X., and Hu, Q., “An Automatic Condition Detection Approach for Quality Assurance in Solar Cell Manufacturing Processes”, IEEE Robotics and Automation Letters, vol. 2, no. 3, pp. 1825 –1831, 2017.

J3. Du, J., Zhang, X., Xu, X., and Shi, J., “A Novel Critical Point Detection Method for Mechanical Deformation in Tightening Processes”, Journal of Manufacturing Systems, vol. 48, pp. 157-165, 2018. 

J4. Du, J., Zhang, X., and Shi, J., “A Condition Change Detection Approach for Solar Conversion Efficiency in Solar Cell Manufacturing Processes”, IEEE Transactions on Semiconductor Manufacturing,  vol. 32, no. 1, pp. 82-92, 2019.

J5.  Du, J., Zhang, X., and Shi, J., “A Physics-based Change Point Detection Method using Torque Signals in Pipe Tightening Processes”, IEEE Transactions on Automation Science and Engineering, vol.16, no. 3, pp. 1289-1300,  2019. 

J6.  Du, J., Yue, X., Hunt, J. H., and Shi, J., “Optimal Placement of Actuators for Composite Fuselage Shape Control via Sparse Learning”, ASME Transactions, Journal of Manufacturing Science and Engineering,  vol. 141, no.10, p. 101004, 2019.

• Best Refereed Paper Finalist Award, INFORMS, the Quality, Statistics and Reliability (QSR) Section, 2018. 

J7. Liu, C., Liu, T., Du, J.*, Zhang, Y., Lai, X., and Shi, J., "Hybrid Nonlinear Variation Modeling of Compliant Metal Plate Assemblies Considering Welding Shrinkage", ASME Transactions, Journal of Manufacturing Science and Engineering, vol. 142, p. 041003, 2020.  

J8. Wang, F., Du, J.*, Zhao, Y., Tang, T., Shi, J., “A Deep Learning based Data Fusion Method for Degradation Modeling and Prognostics ”, IEEE Transactions on Reliability, vol. 70, no. 2, pp. 775-789, 2021. 

J9. Du, J., Liu, C., Liu, J., Zhang, Y., and Shi, J., “Optimal Design of Fixture Layout for Compliant Parts with Application in Ship Assembly”, ASME Transactions, Journal of Manufacturing Science and Engineering, vol. 143, no. 6, p. 061007, 2021. 

J10. Liu, X., Du, J., Ye, Z., “A Condition Monitoring and Fault Isolation System for Wind Turbine based on SCADA Data”, IEEE Transactions on Industrial Informatics, vol. 18, no. 2, pp. 986-995, 2022.  

J11. Du, J., Yan, H., Chang, T., and Shi, J., “A Tensor-Voting Based Surface Anomaly Classification Approach by Using 3D Point Cloud Data”, ASME Transactions, Journal of Manufacturing Science and Engineering, vol. 144, no.5, p. 051005, 2022.

J12. Du, J., Zhang, X., and Ou, W., “Knowledge-Infused Process Monitoring for Quality Improvement in Solar Cell Manufacturing Processes”, Journal of Quality Technology, vol. 54, no. 5, pp. 561-572, 2022.

J13. Wang, A., Du, J., Zhang, X., and Shi, J., “ Ranking Features to Promote Diversity: An Approach Based on Sparse Distance Correlation”, Technometrics, vol. 64, no. 3, pp. 384-395, 2022.

• Best (General) Paper Finalist Award, INFORMS, the Data Mining Section, 2019. 

J14. Du, J.*, Cao, S.,  Hunt, J. H., Huo, X.,  and Shi, J., “A New Sparse-Learning Model for Maximum Gap Reduction of Composite Fuselage Assembly”, Technometrics,  vol. 64, no.3, pp. 409-418, 2022. [arXiv]

• Best (General) Paper Finalist Award, INFORMS, the Data Mining Section, 2020.

J15. Liu, X., Du, J., Ye, Z., “A Covariate-regulated Sparse Subspace Learning Model and Its Application to Process Monitoring and Fault Isolation”, Technometrics,  vol. 65, no.2, pp. 269-280, 2023. 

J16. Liu, P., Du, J., Zang, Y., Zhang, C., and Wang, K., “In-profile Monitoring for Cluster-Correlated Data in Advanced Manufacturing System”, Journal of Quality Technology, vol. 55, no. 2, pp. 195-219, 2023. 

• Best Student Paper Award Finalist, IISE, the Quality Control and Reliability Engineering Division, 2021. 

J17. Tao, C.#, Du, J.*, and Chang, T., “Anomaly Detection for Fabricated Artifact by Using Unstructured 3D Point Cloud Data”, IISE Transactions, in press, 2022. 

• Best Student Paper Award Finalist, IISE, the Quality Control and Reliability Engineering Division, 2022.

• Editor's Choice to an IISE Transactions Invited Session at INFORMS 2023.

J18. Li, Y.#, Du, J.*, and Jiang, W., “Reinforcement Learning for Process Control with Application in Semiconductor Manufacturing”, IISE Transactions, (just-accepted), 1-25, 2023. [arXiv]

J19. Xie, Y.#, Du, J.*, and Wu, J., “APFC: Adaptive Particle Filter for Change Point Detection of Profile Data in Manufacturing Systems”, IEEE Transactions on Automation Science and Engineering, 2023. 

J20. Tao, C.#, and Du, J.*, “PointSGRADE: Sparse Learning with Graph Representation for Anomaly Detection by Using Unstructured 3D Point Cloud Data”, IISE Transactions, (just-accepted), 1-22, 2023. 

J21. Hong, G., Gao, S., Xia, T., Du, J., Jin, X., Pan, E., and Xi, L. Fixture layout optimization of large compliant ship part assembly for reducing and straightening butt clearance. Engineering Optimization, 1-20, 2023.

J22. Li, Y.#, Du, J.*, Tsung, F., & Jiang, W., “Tensor-based process control and monitoring for semiconductor manufacturing with unstable disturbances”, Naval Research Logistics (NRL), 1–16, https://doi.org/10.1002/nav.22228, 2024. 

J23. Li, Y.#, Du, J.*, Jiang, W., and Tsung, F., “MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference”, IISE Transactions, 1-15, 2024. 

• 2024 INFORMS ICQSR Best Paper Award Finalist, only 4 papers are selected as Finalist

J24. Wang, Y., Lutz, T O, Yue, X. and Du, J., “SmartFixture: Physics-guided Reinforcement Learning for Automatic Fixture Design in Manufacturing Systems”, IISE Transactions, accepted, 1-20, 2024. 

J25. Tao, C.#, Du, J.*, and Liu, J., “Optimal Placement of Programmable Toolings Considering Hierarchical Structure via Sparse Learning in Multistage Assembly Processes”, IEEE Transactions on Automation Science and Engineering, accepted, 2024.

J26. Du, J.*, Tao, C.#, Cao, X.#, and Tsung, F., “3D Vision-based Anomaly Detection in Manufacturing: A Survey”, Frontiers of Engineering Management, 1-18, 2025. (Invited Paper, FEM Journal is established from Chinese Academy of Engineering) 

J27. Cao, X.#, Tao, C.#, and Du, J.*, “3D-CSAD: Untrained 3D Anomaly Detection for Complex Manufacturing Surfaces”, ASME Journal of Computing and Information Science in Engineering, accepted, 2025.  (Invited Paper, Special issue on Geometric Data Processing and Analysis for Advanced Manufacturing) 

J28. Ye, P.#, Tao. C#, and Du, J.*, “A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection”, IISE Transactions, 2025. 

• 2023 Best Paper Award from Reliability Division of Chinese Society of Operations Research  

• 2024 Best Application Paper-First Prize at CSIE&CIEDH

J29. Cao, X.#, Tao, C.#, Cheng, Y.#, and Du, J.*, “IAENet: An Importance-Aware Ensemble Model for 3D Point Cloud-Based Anomaly Detection", Information Fusion, online, 2025.

J30. Wang, A., Yan, H., and Du, J., “Interpretation and Visualization of Distance Covariance through Additive Decomposition of Correlations Formula”, INFORMS Journal on Data Science,  accepted, 2026. (arXiv preprint arXiv:2305.14767)

• 2023 Best Track Paper Award, IISE, the Data Analytics and Information Systems (DAIS) Section.

J31. Xu, H.#, Du, J.*, Wang, A., and Chen, Y., “Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches”, INFORMS Journal on Data Science,  under 2nd round of review. (arXiv preprint arXiv:2309.11120)

J32. Du, J.*, Xie, Y.#, and Zhang, C., “Deep Metric Learning for Defect Classification of Threaded Pipe Connections using Multichannel Partially Observed Functional Data”, Journal of Quality Technology,  under 2nd round of revision. (arXiv preprint arXiv:2404.03329).

J33. Ye, P.# and Du, J.*, “SAPO-RL: Sequential Actuator Placement Optimization for Fuselage Assembly via Reinforcement Learning”, IISE Transactions, under 2nd round of review. (arXiv preprint arXiv:2504.17603).

• 2025 Best Track Paper Award, IISE, the Data Analytics and Information Systems (DAIS) Section.

J34. Cao, X.#, Tao, C.#, and Du, J.*, “Deep subspace learning for anomaly classification by using 3D point cloud data”, arXiv preprint arXiv:2502.11669. 

• 2023 Data Challenge Winner, IISE, the Data Analytics and Information Systems (DAIS) Section.

J35. Li, Y.#, Ye, Z.*, Tsung, F., Jiang, W., and Du, J. “Model-based Prior for Model-free Reinforcement Learning in Process Control: An Offline Methodology for Semiconductor Manufacturing", Technometrics,  under 2nd round of review. 

J36. Du, J., Xie, Y.#, Wang, J., and Bai, L.#, “Crucial Variable Identification for Quality Improvement of Ceramic Firing Process: Algorithms and Applications”, major revision.  

• 2024 CSAMSE Annual Conference Best Practice Award 2nd Prize 

J37. Du, J.*, and Chen, D.#, “Position: Untrained Machine Learning for Anomaly Detection”. arXiv preprint arXiv:2502.03876, 2025. 

J38. Cao, J.#, Zhou, K., and Du, J.*, 2025, “HyPCV-Former: Hyperbolic Spatio-Temporal Transformer for 3D Point Cloud Video Anomaly Detection”. arXiv preprint arXiv:2508.00473.

J39. Cheng, Y.# and Du, J.*, “3D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noise”, arXiv preprint arXiv:2504.12856.

J40. Tao, C.#, Xu, H.#, and Du, J.*, “F2PAD: A General Optimization Framework for Feature-Level to Pixel-Level Anomaly Detection”, arXiv preprint arXiv:2407.06519.

Peer Review Conference 

C1. Tao, C.#, Cao, X.#, & Du, J.* (2025). G $^{2} $ SF-MIAD: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 20551-20560, Honolulu, USA. (acceptance rate: 24%)

C2.  Xie, Y.#, Du, J.*, Tsung, F., Wan, P., and Xu, G., 2024, “FIT3D: Real-time Flatness Inspection Algorithm of Ceramic Tiles using Structured Light 3D Scanner”, IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 897-903, Bari, Italy.

Invited to submit an extended paper for consideration in the IEEE Transactions on Automation Science and Engineering.

C3.  Du, J. and Zhang, X., 2016, “A Critical Change Point Detection Method in Threaded Steel Pipe Connection Processes Using Two Stage Sequential Piecewise Linear Approach”, Proceedings of the 11th Conference on Manufacturing Science and Engineering, Vol. 49903, p. V002T04A029, Blacksburg, USA.

C4.  Lin, G., Luo, X., Du, J., and Tan, H., 2014, “A hybrid inflatable boom/rigid hinge membrane cylindrical reflector”, Proceedings of the 2nd International Scientific Conference on Advanced Lightweight Structures and Reflector Antennas, Tbilisi, Georgia.

PhD Thesis

Du, J., "Profile Data Analytics for Change Point Detection in Manufacturing Systems", Doctoral Thesis, Peking University, 2019. 

• Outstanding Doctoral Thesis Award, Chinese Society of Management Science and Engineering, 2020.  

• Outstanding Doctoral Thesis Award, Peking University, 2019.