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Zheng Wang, Associate Professor

         Personal Profile         

Zheng Wang, Associate Professor



Academic Homepage: [Google Scholar] [DBLP]

Research Interests: multimodal cognitive computing, deep representation learning,

time series data analysis, 3D point cloud analysis, robust machine learning

Contact Address: Northwestern Polytechnical University, No. 127, Youyi West Road, Beilin District, 

Xi'an, Shaanxi Province

Postal Code: 710072

Email: zhengwangml AT gmail.com







        Work Experience      

2017-2021Northwestern Polytechnical UniversityPh.D

2021-2023Xi'an Jiaotong UniversityPost-Doc
2023-NowNorthwestern Polytechnical UniversityAssociate Professor 

     Recent Publications     

Representative works:

  1. Z. Wang, F. Nie, C. Zhang, R. Wang and X. Li, "Worst-case Discriminative Feature Learning via Max-Min Ratio Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, (CCF A, IF: 17.861), 2024.  [BibTeX]|[PDF]

  2. F. Nie, Z. Wang, R. Wang, Z. Wang and X. Li, "Towards Robust Discriminative Projections Learning via Non-greedy L2,1-Norm MinMax," IEEE Transactions on Pattern Analysis and Machine Intelligence, (CCF A, IF: 17.861), 2020.  [BibTeX]|[PDF]

  3. Z. Wang, F. Nie, H. Wang, H. Huang and F. Wang, "Toward Robust Discriminative Projections Learning Against Adversarial Patch Attacks," IEEE Transactions on Neural Networks and Learning Systems, in press, 2023.  [BibTeX]|[PDF]

  4. Z. Wang, Y. Yuan, R. Wang, F. Nie, Q. Huang and X. Li, "Pseudo-Label Guided Structural Discriminative Subspace Learning for Unsupervised Feature Selection," IEEE Transactions on Neural Networks and Learning Systems, in press, 2023.  [BibTeX]|[PDF]

  5. Z. Wang, Q. Li, F. Nie, R. Wang, F. Wang and X. Li, "Efficient Local Coherent Structure Learning via Self-Evolution Bipartite Graph," IEEE Transactions on Cybernetics, in press, 2023.  [BibTeX]|[PDF]

  6. Z. Wang, D. Wu, R. Wang, F. Nie and F. Wang, "Joint Anchor Graph Embedding and Discrete Feature Scoring for Unsupervised Feature Selection," IEEE Transactions on Neural Networks and Learning Systems, in press, 2022.  [BibTeX]|[PDF]

  7. Z. Wang, F. Nie, L. Tian, R. Wang and X. Li, "Discriminative feature selection via a structured sparse subspace learning module,"  Proceedings of the International Joint Conference on Artificial Intelligence - Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI, CCF A), in press, 2020. [BibTeX]|[PDF]

  8. Z. Wang, Q. Li, H. Zhao and F. Nie, "Simultaneous local clustering and unsupervised feature selection via strong space constraint," Pattern Recognition, in press, 2023. [BibTeX]|[PDF]

  9. Z. Wang, J. Xie, R. Wang, F. Nie, X. Li, "Adaptive Graph Convolutional Network for Unsupervised Generalizable Tabular Representation Learning," IEEE Transactions on Neural Networks and Learning Systems, in press, 2024.[PDF]

  10. L Tang, Z. Wang(Corresponding author), G He, R Wang, F Nie, "Perturbation Guiding Contrastive Representation Learning for Time Series Anomaly Detection", Proceedings of the International Joint Conference on Artificial Intelligence-Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI, CCF A), 2024.[PDF]

  11. L Tang, Z. Wang(Corresponding author), J. Wang, G He, Z. Hao, R Wang, F Nie, "Language Pre-training Guided Masking Representation Learning for Time Series Classification", Association for the Advancement of Artificial Intelligence (AAAI, CCF A), 2025.

  12. D. Hu, Z. Wang(Corresponding author), F. Nie, R. Wang and X. Li, "Self-Supervised Learning for Heterogeneous Audiovisual Scene Analysis," IEEE Transactions on Multimedia, 2023. [BibTeX]|[PDF]

  13. G He, Z. Wang(Corresponding author), L. Tang, F. Nie, X. Li, "Reweighted-Boosting: A Gradient-Based Boosting Optimization Framework", IEEE Transactions on Neural Networks and Learning Systems, in press, 2024.[PDF]

  14. F. Nie, Z. Wang, R. Wang and X. Li, "Adaptive Local Embedding Learning for Semi-supervised Dimensionality Reduction," IEEE Transactions on Knowledge and Data Engineering, (CCF A), 2021.  [BibTeX]|[PDF]

  15. F. Nie, Z. Wang, T. Lai, R. Wang and X. Li, "Subspace Sparse Discriminative Feature Selection," IEEE Transactions on Cybernetics, 2020.  [BibTeX]|[PDF]

Co-supervised with Prof. Nie:

  1. H. Nie, Q. Li, Z. Wang(Corresponding author), H. Zhao and F. Nie, "Semisupervised Subspace Learning With Adaptive Pairwise Graph Embedding," IEEE Transactions on Neural Networks and Learning Systems, in press, 2023. [BibTeX]|[PDF]

  2. S. Wang, F. Nie, Z. Wang, R. Wang and X. Li, "Outliers Robust Unsupervised Feature Selection for Structured Sparse Subspace," IEEE Transactions on Knowledge and Data Engineering, in press, (CCF A), 2023. [BibTeX]|[PDF]

  3. S. Wang, F. Nie, Z. Wang, R. Wang and X. Li, "Sparse robust subspace learning via boolean weight," Information Fusion, 2023.  [BibTeX]|[PDF]

  4. Y. Yuan, Z. Wang, F. Nie and X. Li, "Unsupervised Feature Selection with self-Weighted and L2, 0-Norm Constraint," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. [BibTeX]|[PDF]

  5. S. Wang, F. Nie, Z. Wang, R. Wang and X. Li, "Robust Principal Component Analysis via Joint Reconstruction and Projection," IEEE Transactions on Neural Networks and Learning Systems, in press, 2022. [BibTeX]|[PDF]

  6. F. Nie, C. Zhang, Z. Wang, R. Wang and X. Li, "Local Embedding Learning via Landmark-Based Dynamic Connections," IEEE Transactions on Neural Networks and Learning Systems, , 2023. [BibTeX]|[PDF]

  7. R. Wang, C. Zhang, J. Bian, Z. Wang, F. Nie and X. Li, "Sparse and Flexible Projections for Unsupervised Feature Selection," IEEE Transactions on Knowledge and Data Engineering, , 2023. [BibTeX]|[PDF]

  8. F. Nie, S. Wang, Z. Wang, R. Wang and X. Li, "Discrete Robust Principal Component Analysis via Binary Weights Self-Learning," IEEE Transactions on Neural Networks and Learning Systems, , 2023. [BibTeX]|[PDF]

Co-authored:

  1. Z. Zhao, R. Wang, Z. Wang, F. Nie and X. Li, "Graph Joint Representation Clustering via Penalized Graph Contrastive Learning," IEEE Transactions on Neural Networks and Learning Systems, , 2023. [BibTeX]|[PDF]

  2. Q. Wang, F. Wang, Z.Li, Z. Wang and F. Nie, "Coordinate Descent Optimized Trace Difference Model for Joint Clustering and Feature Extraction,"  Pattern Recognition, , 2023. [BibTeX]|[PDF]

  3. Y. Guo, Y. Sun, Z. Wang, F. Nie and F. Wang, "Double-Structured Sparsity Guided Flexible Embedding Learning for Unsupervised Feature Selection," IEEE Transactions on Neural Networks and Learning Systems, 2023. [BibTeX]|[PDF]

  4. Z. Li, F. Nie, D. Wu, Z. Wang and X. Li, "Sparse Trace Ratio LDA for Supervised Feature Selection," IEEE Transactions on Cybernetics,in press, 2023.[BibTeX]|[PDF]

[more]

    Academic activities     

  • Journal and conference reviewer: IEEE Trans-NNLS, IEEE Trans-CYB, Pattern Recognition, AAAI, IJCAI, ICLR, NeurIPS, ICML, etc.

  • Won the "Academic Rising Star" Award at the IJCAI-SAIA Youth Elite Academic Conference

  • Host the National Natural Science Foundation Youth Project

  • Host the 70th batch of Chinese postdoctoral general projects

  • Host the Shaanxi Province Natural Science Basic Research Program Youth Project

  • Host several military vertical and horizontal projects


    Other Information     

  • Welcome to apply. I will personally provide one-on-one guidance in terms of model conception, code programming, article writing, etc. Interested students please send your resume to zhengwangml AT gmail.com.


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