Name：Zhiwen Yu
Professional Title / Position：Professor
Research Direction：Artificial intelligence, data mining, machine learning (ensemble learning, broad learning system, imbalanced learning, semi-supervised learning, and so on )
Team：Data science and artificial intelligence
Tel：/
Email：zhwyu@scut.edu.cn
Biography：
Zhiwen Yu (S'06-M'08-SM'14) is a Professor in School of Computer Science and Engineering, South China University of Technology, China. He received the Ph.D. degree from the City University of Hong Kong, Hong Kong, in 2008. Dr. Yu has authored or coauthored more than 200 refereed journal articles and international conference papers, including more than 90 articles in the journals of IEEE Transactions, h-index 57，Google citation 17000. He is an Associate Editor of the IEEE Transactions on systems, man, and cybernetics: systems, IEEE Transactions on Neural Networks and Learning Systems and the informatics journal. Dr. Yu is in charge of or take part in more than 30 research projects, such as the National Natural Science Foundation of China (the Key Program、the General Program and the Youth Program), National Natural Science Foundation of China for Excellent Young Scientists, the Key R&D Program of Guang Dong Province, and so on. He is a senior member of IEEE and ACM, a Member of the Council of China Computer Federation from 2016 to 2023 (CCF). Ranked among the top 2% of scientists worldwide in Stanford University's 2024 World's Top 2% Scientists List.
Example：
I received my B.S. degree in Computer Science at Nanjing University in 1999, and my PhD in Computer Science at Nanjing University in 2005. I joined the Nanjing University as an assistant professor in 2005 , worked as an associate professor from 2008, and obtained professor in 2017. I have been on leave from Nanjing University from August 2010 to September 2011 to visit EECS Department and Statistics Department at UC Berkeley.
Education：
2008 City University of Hong Kong PhD
2005 Sun Yat-Sen University Master
2001 Sun Yat-Sen University Bachelor
Work Experience：
年份//学校/学位
2009 South China University of Technology Lecture
2010 South China University of Technology Associate professor
2015 South China University of Technology Professor
Course：
Neural network and deep learning, Database
Projects：
1. General Program of National Natural Science Foundation of China (No. 62572199), Research on Robust Multimodal Learning in Open and Incomplete Scenarios, 2026/01–2029/12, Ongoing, Principal Investigator (PI)
2. Major Research Plan of National Natural Science Foundation of China (No. 92467109), Research on Reliable Multimodal Learning and Inference for Industrial Internet, 2025-01-01–2027-12-31, Ongoing, Principal Investigator (PI)
3. Key Program of National Natural Science Foundation of China (AI Emergency Special Program, No. 61751205), Decision Feature Extraction and Knowledge Discovery from Multi-source Heterogeneous Data, 2018/01–2020/12, Completed, Principal Investigator (PI)
4. National Excellent Youth Science Foundation of China (No. 61722205), Ensemble Learning Theory and Applications*, 2018/01–2020/12, Completed, Principal Investigator (PI)
5. General Program of National Natural Science Foundation of China (No. 61572199), Research on Semi-supervised Clustering Ensemble Based on Derived Distance Mathematical Models, 2016/01–2019/12, Completed, Principal Investigator (PI)
6. Young Scientists Fund of National Natural Science Foundation of China (No. 61003174), A Novel Framework for Pattern Discovery in Cancer Gene Expression Data Based on Clustering Ensemble Algorithms, 2011/01–2013/12, Completed, Principal Investigator (PI)
7. Key Research and Development Program of Guangdong Province (No. 2018B010107002), Research on Cognitive Theory for Multimodal Data in Intelligent Manufacturing, 2019/01–2021/12, Completed, Principal Investigator (PI)
8. Guangdong Science and Technology Program (Guangdong-Hong Kong Cooperation Project, No. 2016A050503015), Research on Complex Event Mining from Media Big Data, 2016/05–2018/05, Completed, Principal Investigator (PI)
9. Guangdong Science and Technology Program (International Cooperation Project, No. 2015A050502011), Application Research of Ensemble Learning Algorithms in Multivariate Urban Data Fusion and Mining, 2016/01–2017/12, Completed, Principal Investigator (PI)
10. Guangdong Natural Science Foundation for Distinguished Young Scholars (No. S2013050014677), Pattern Discovery and Its Applications, 2013/10–2016/09, Completed, Principal Investigator (PI)
Publications：
1. Mianfeng Lin, Zhiwen Yu, Kaixiang Yang, C. L. Philip Chen, Dynamic Chunk-Based Active Learning Based on Enhanced Broad Learning System for Imbalanced Drifting Data Streams, IEEE Transactions on Knowledge and Data Engineering, vol. 38, no. 2, pp. 997-1010, Feb. 2026.
2. Wuxing Chen, Zhiwen Yu, Kaixiang Yang, Ziwei Fan, C. L. Philip Chen, Adaptive Weighted Double Uncertainty Incrementally Active Learning for Multi-Class Imbalanced Data, IEEE Transactions on Knowledge and Data Engineering, vol. 38, no. 2, pp. 827-841, Feb. 2026.
3. Guojie Li, Zhiwen Yu, Kaixiang Yang, C. L. Philip Chen, Xuelong Li, “Ensemble-Enhanced Semi-Supervised Learning With Optimized Graph Construction for High-Dimensional Data”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.47, no.2, pp. 1103-1119, 2025.
4. Yuanxin Lin, Zhiwen Yu, Kaixiang Yang, C. L. Philip Chen, Ensemble Denoising Autoencoders Based on Broad Learning System for Time-Series Anomaly Detection, in IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 8, pp: 13913-13926, 2025.
5. Zhijie Zhong, Zhiwen Yu, Kaixiang Yang, Ziwei Fan, C. L. Philip Chen, Adaptive Memory Broad Learning System for Unsupervised Time Series Anomaly Detection, IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 5, pp. 8331-8345, 2025.
6. Zhijie Zhong, Zhiwen Yu, Xing Xi, Yue Xu, Wenming Cao, Yiyuan Yang, Kaixiang Yang, Jane You, “SimAD: A Simple Dissimilarity-Based Approach for Time-Series Anomaly Detection”, IEEE Transactions on Neural Networks and Learning Systems, vol.36, no.11, pp.19669-19680, 2025.
7. Xu Chen, Zhiwen Yu, Ziwei Fan, Kaixiang Yang, C. L. Philip Chen, “Adaptive Dictionary Learning for Multiview Subspace Clustering”, IEEE Transactions on Cybernetics, vol. 55, no.6, pp. 2833-2843, 2025.
8. Zhijie Zhong, Zhiwen Yu, Yiyuan Yang, Weizheng Wang, Kaixiang Yang, C. L. Philip Chen, “PatchAD: A Lightweight Patch-Based MLP-Mixer for Time Series Anomaly Detection”, IEEE Trans. Big Data, vol.11, no.(6), pp. 3460-3473, 2025.
9. Zhiwen Yu, Siyong Huang, Kaixiang Yang, Jianming Lv, C. L. Philip Chen, “Ensemble Approaches for Dynamic Data Stream Classification Under Label Scarcity”, IEEE Transactions Big Data, vol.11, no.6, pp. 3047-3060, 2025.
10. Mianfen Lin, Zhiwen Yu, Kaixiang Yang, C. L. Philip Chen, “Hybrid Ensemble Framework for Imbalanced Data Streams With Concept Drift”, IEEE Transactions Big Data, vol. 11, no.6, pp. 3430-3442, 2025.
11. Guojie Li, Zhiwen Yu, Kaixiang Yang, Ziwei Fan, C. L. Philip Chen, “Incremental Semisupervised Learning With Adaptive Locality Preservation for High-Dimensional Data”, IEEE Transactions Artificail Intelligence , vol.6, no.11, pp. 2990-3004, 2025.
12. Wuxing Chen, Kaixiang Yang, Zhiwen Yu, Feiping Nie, C. L. Philip Chen, “Adaptive Broad Network With Graph-Fuzzy Embedding for Imbalanced Noise Data”, IEEE Transactions on Fuzzy Systems, vol. 33, no. 6, pp. 1949-1962, 2025.
13. Xiaoqing Liu, Zhiwen Yu, Kaixiang Yang, Jun Yu, Huanqiang Zeng, C. L. Philip Chen, “Enhanced Cross-Modal Hashing via Hybrid Distillation and Structural Refinement”, IEEE Trans. Image Process, vol.34, pp. 7138-7151, 2025.
14. Ziwei Fan, Zhiwen Yu, Kaixiang Yang, Wuxing Chen, Xiaoqing Liu, Guojie Li, Xianling Yang, C. L. Philip Chen, “Diverse Models, United Goal: A Comprehensive Survey of Ensemble Learning”, CAAI Transactions Intelligent Technology, vol.10, no.4, pp. 959-982, 2025.
15. Xiaoqing Liu, Huanqiang Zeng, Yifan Shi, Jianqing Zhu, Kaixiang Yang, Zhiwen Yu, “Ensemble Prototype Networks for Unsupervised Cross-Modal Hashing With Cross-Task Consistency”, IEEE Transactions Multimedia, Vol. 27, no. 3476-3488, 2025.
16. Cheng Liu, Rui Li, Hangjun Che, Man-Fai Leung, Si Wu, Zhiwen Yu, Hau-San Wong, “Beyond Euclidean Structures: Collaborative Topological Graph Learning for Multiview Clustering”, IEEE Transactions on Neural Networks and Learning Systems, Vol.36, no.6, pp. 10606-10618, 2025.
17. Man Li, Ming-yang Jiang, Wenming Cao, Mingming Yang, Zhiwen Yu, “Heterogeneous Propagation-Based Recommendation Systems with Knowledge Graph Attention Network”. IEEE Transactions Comput. Soc. Syst., vol.12, no.5, pp. 3230-3242, 2025.
18. Zhiwen Yu, Zhijie Zhong, Kaixiang Yang, Wenming Cao, C. L. Philip Chen, “Broad Learning Autoencoder with Graph Structure for Data Clustering”, IEEE Transactions on Knowledge and Data Engineering, vol.36, no.1, pp. 49-61, 2024.
19. Yuhong Xu, Zhiwen Yu, C. L. Philip Chen, “Improved Contraction-Expansion Subspace Ensemble for High-Dimensional Imbalanced Data Classification”, IEEE Transactions on Knowledge and Data Engineering, vol.36, no.10, pp. 5194-5205, 2024.
20. Guojie Li, Zhiwen Yu, Kaixiang Yang, Mianfen Lin, C. L. Philip Chen, “Exploring Feature Selection with Limited Labels: A Comprehensive Survey of Semi-Supervised and Unsupervised Approaches”; IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 11, pp. 6124-6144, 2024.
21. Kaixiang Yang, Zhiwen Yu, Wuxing Chen, Zefeng Liang, C. L. Philip Chen, “Solving the Imbalanced Problem by Metric Learning and Oversampling”, IEEE Transactions on Knowledge and Data Engineering, vol.36, no.12, pp. 9294-9307, 2024.
22. Kaixiang Yang, Wuxing Chen, Yifan Shi, Zhiwen Yu, C. L. Philip Chen, “Simplified Kernel-Based Cost-Sensitive Broad Learning System for Imbalanced Fault Diagnosis”, IEEE Trans. Artif. Intell., vol.5, no.12, pp. 6629-6644, 2024.
23. Fan Yun, Zhiwen Yu, Kaixiang Yang, C. L. Philip Chen, “AdaBoost-Stacking Based on Incremental Broad Learning System”, . .IEEE Transactions on Knowledge and Data Engineering, vol.36, no.12, pp. 7585-7599, 2024.
24. Yuhong Xu, Zhiwen Yu*, C. L. Philip Chen, “Classifier Ensemble Based on Multiview Optimization for High-Dimensional Imbalanced Data Classification,” IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 1, pp.870-883, 2024.
25. Yifan Shi, Zhiwen Yu*, C. L. Philip Chen, Huanqiang Zeng, “Consensus Clustering with Co-Association Matrix Optimization,” IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 3, pp. 4192-4205, 2024.
26. Mianfen Lin, Kaixiang Yang, Zhiwen Yu, Yifan Shi, C. L. Philip Chen, “Hybrid Ensemble Broad Learning System for Network Intrusion Detection”, IEEE Trans. Ind. Informatics, vol.20, no.4, pp.5622-5633, 2024.
27. Guoliang He, Lifang Dai, Zhiwen Yu, C. L. Philip Chen, “GAN-Based Temporal Association Rule Mining on Multivariate Time Series Data”, IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 10, pp. 5168-5180, 2024.
28. Guoliang He, Dawei Jin, Lifang Dai, Xin Xin, Zhiwen Yu, C. L. Philip Chen, “Online Learning of Temporal Association Rule on Dynamic Multivariate Time Series Data”, IEEE Transactions on Knowledge and Data Engineering, vol.36, no.12, pp.8954-8966, 2024.
29. Cheng Liu, Rui Li, Hangjun Che, Man-Fai Leung, Si Wu, Zhiwen Yu, Hau-San Wong, “Latent Structure-Aware View Recovery for Incomplete Multi-View Clustering”, IEEE Transactions on Knowledge and Data Engineering, vol.36, no.12, pp. 8655-8669, 2024.
30. Cheng Liu, Rui Li, Si Wu, Hangjun Che, Dazhi Jiang, Zhiwen Yu, Hau-San Wong, “Self-Guided Partial Graph Propagation for Incomplete Multiview Clustering”, IEEE Transactions on Neural Networks and Learning Systems, vol.35, no.8, pp. 10803-10816, 2024.
31. Dan Dai, Zhiwen Yu*, Weijie Huang, Yang Hu, C.L.Philip Chen, “Multi-Objective Cluster Ensemble Based on Filter Refinement Scheme”, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no.8, pp. 8257-8269, 2023.
32. Yuhong Xu, Zhiwen Yu*, Wenming Cao, C. L. Philip Chen, A Novel Classifier Ensemble Method Based on Subspace Enhancement for High-Dimensional Data Classification, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 1, pp. 16-30, 2023.
33. Yuhong Xu, Zhiwen Yu*, C. L. Philip Chen, Zhulin Liu, “Adaptive Subspace Optimization Ensemble Method for High-Dimensional Imbalanced Data Classification”, IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 5, pp. 2284-2297, 2023.
34. Kaixiang Yang, Yuchen Liu, Zhiwen Yu∗, C. L. Philip Chen, “Extracting and Composing Robust Features with Broad Learning System”, IEEE Transactions on Knowledge and Data Engineering, vol. 35, no.4, pp. 3885-3896, 2023.
35. Yifan Shi, Kaixiang Yang, Zhiwen Yu, C. L. Philip Chen, Huanqiang Zeng, “Adaptive Ensemble Clustering With Boosting BLS-Based Autoencoder”, IEEE Transactions on Knowledge and Data Engineering, vol.35, no.12, pp.12369-12383,2023.
36. Kaixiang Yang, Yifan Shi, Zhiwen Yu, Qinmin Yang, Arun Kumar Sangaiah, Huanqiang Zeng, “Stacked One-Class Broad Learning System for Intrusion Detection in Industry 4.0”, IEEE Transactions on Industrial Informatics, vol. 19, no.1, pp. 251-260, 2023.
37. Liu Cheng, Wu Si, Jiang Dazhi, Yu Zhiwen, Wong Hau-San, View-Aware Collaborative Learning for Survival Prediction and Subgroup Identification, IEEE Transactions on Biomedical Engineering, vol. 70, no.1, pp. 307-317, 2023.
38. Zhiwen Yu, Zhongfan Zhang, Wenming Cao, C. L. Philip Chen, Cheng Liu, Hau-San Wong, “ GAN-Based Enhanced Deep Subspace Clustering Networks ”, IEEE Transactions on Knowledge and Data Engineering, vol.34, no. 7, 3267 - 3281, 2022.
39. Kaixiang Yang, Zhiwen Yu*, C. L. Philip Chen, Wenming Cao, Jane J. You, Hau-San Wong, “Incremental Weighted Ensemble Broad Learning System For Imbalanced Data”, IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 12, pp. 5809-5824, 2022.
40. Zhiwen Yu, Fengxu Ye, Wenming Cao, Kaixiang Yang, C. L. Philip Chen, Lianglun Cheng, Jane You, Hau-San Wong, “Semi-Supervised Classification with Novel Graph Construction for High Dimensional Data”, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 1, pp. 75-88, 2022..
41. Cheng Liu, Wenming Cao, Si Wu, Wenjun Shen, Dazhi Jiang, Zhiwen Yu, Hau-San Wong, “Asymmetric Graph-Guided Multi-Task Survival Analysis with Self-Paced Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 2, pp. 654-666, 2022.
42. Zhiwen Yu, Daxing Wang, Xian-Bing Meng, C. L. Philip Chen, “Clustering Ensemble Based On Hybrid MultiView Clustering”, IEEE Transactions on Cybernetics, vol. 52, no. 7, pp. 6518-6530, 2022.
43. Yuhong Xu, Zhiwen Yu*, Wenming Cao, C. L. Philip Chen, “Adaptive Dense Ensemble Model for Text Classification”, IEEE Transactions on Cybernetics, vol. 52, no. 8, pp. 7513-7526, 2022.
44. Zhiwen Yu, Kankan Lan, Zhulin Liu, Guoqiang Han, “Progressive Ensemble Kernel-Based Broad Learning System for Noisy Data Classification”, IEEE Transactions on Cybernetics, vol. 52, no. 9, pp. 9656-9669, 2022.
45. Jian Zhong, Xiangping Zeng, Wenming Cao, Si Wu, Cheng Liu, Zhiwen Yu, Hau-San Wong, “Semi-Supervised Multiple Choice Learning for Ensemble Classification”, IEEE Transactions on Cybernetics, vol. 52, no. 5, pp. 3658-3668, 2022.
46. Yang Hu, Guihua Wen, Mingnan Luo, Dan Dai, Wenming Cao, Zhiwen Yu, Wendy Hall, “Inner-Imaging Networks: Put Lenses Into Convolutional Structure”, IEEE Transactions on Cybernetics, Vol. 52, no. 8, pp. 8547-8560, 2022.
47. Zhiwen Yu, Kaixiang Yang, Philip Chen, Wenming Cao, Hau-San Wong, Jane You, Guoqiang Han,“Progressive hybrid classifier ensemble for imbalanced data”， IEEE Transactions on Systems, Man, and Cybernetics: Systems，vol. 52, no.4, pp. 2464-2478, 2022.
48. Cheng Liu, Wenming CAO, Si Wu, Wenjun Shen, Dazhi Jiang, Zhiwen Yu, Hau-San Wong, “Supervised graph clustering for cancer subtyping based on survival analysis and integration of multi-omic tumor data”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.19, no.2, pp. 1193-1202, 2022.
49. Yuhong Xu, Zhiwen Yu*, Wenming Cao, C. L. Philip Chen, Jane You, Adaptive Classifier Ensemble Method Based on Spatial Perception for High-Dimensional Data Classification, IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 7, pp. 2847-2862, 2021.
50. Yifan Shi, Zhiwen Yu*, Wenming Cao, C. L. Philip Chen, Hau-San Wong, Guoqiang Han, “Fast and Effective Active Clustering Ensemble Based on Density Peak”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 8, pp. 3593-3607, 2021.
51. Yang Hu, Guihua Wen, Huiqiang Liao, Changjun Wang, Dan Dai, Zhiwen Yu, “Automatic construction of Chinese herbal prescription from tongue image via CNNs and auxiliary latent therapy topics”, IEEE Transactions on Cybernetics, vol.51, no. 2, pp. 708-721, 2021.
52. Dan Dai, Juan Tang, Zhiwen Yu*, Hau-San~Wong, Jane You, Wenming Cao, Yang Hu, C. L. Philip Chen,“An Inception Convolutional AutoEncoder Model for Chinese Healthcare Question Clustering”，IEEE Transactions on Cybernetics, vol. 51, no. 4, pp. 2019-2031, 2021.
53. Jun Wang, Xing Wang, Guoxian Yu, Carlotta Domeniconi, Zhiwen Yu, Zili Zhang, Discovering Multiple Co-Clusterings with Matrix Factorization, IEEE Transactions on Cybernetics, vol. 51, no. 7, pp. 3576-3587, 2021.
54. Qianli Ma, Enhuan Chen, Zhenxi Lin, Jiangyue Yan, Zhiwen Yu, Wing W. Y. Ng, “Convolutional Multitimescale Echo State Network”，IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1613-1625, 2021.
55. Yewang Chen, Lida Zhou, Songwen Pei, Zhiwen Yu, Yi chen, Xin Liu, Jixiang Du and Naixue Xiong,“KNN-BLOCK DBSCAN: Fast Clustering For Large Scale Data”， IEEE Transactions on Systems, Man, and Cybernetics: Systems， vol. 51, no. 6, pp. 3939-3953, 2021.
56. Kaixiang Yang, Zhiwen Yu*, Xin Wen, Wenming Cao, C. L. Philip Chen, Hau-San Wong, Jane You, “Hybrid Classifier Ensemble for Imbalanced Data”, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 4, pp. 1387-1400, 2020.
57. Cheng Liu, Chu Tao Zheng, Si Wu, Zhiwen Yu and Hau-San Wong, “Multitask Feature Selection by Graph-Clustered Feature Sharing”, IEEE Transactions on Cybernetics, vol.50, no.1, pp. 74-86, 2020.
58. Yifan Shi, Zhiwen Yu*, C. L. Philip Chen, Jane You, Hau-San Wong, Yide Wang，“Transfer clustering ensemble selection”，IEEE Transactions on Cybernetics, vol. 50, no. 6, pp. 2872-2885, 2020.
59. Qianli Ma, Sen Li, Lifeng Shen, Jiabing Wang, Jia Wei, Zhiwen Yu, Garrison W. Cottrell, “End-to-End Incomplete Time-Series Modeling From Linear Memory of Latent Variables”, IEEE Transactions on Cybernetics, vol.50, no.12, pp. 4908-4920, 2020.
60. Jichang Li, Si Wu, Cheng Liu, Zhiwen Yu, and Hau-San Wong , “Semi-Supervised Deep Coupled Ensemble Learning with Classification Landmark Exploration”，IEEE Transactions on Image Processing, vol. 29, no. 1, pp. 538-550, 2020.
61. Si Wu，Wenhao Wu，Shiyao Lei，Sihao Lin，Rui Li，Zhiwen Yu，Hau-San Wong，“Semi-Supervised Human Detection via Region Proposal Networks Aided by Verification”，IEEE Transactions on Image Processing, vol. 29, pp. 1562 - 1574, 2020.
62. Wenming Cao, Si Wu, Zhiwen Yu, Hau-San Wong, Exploring Correlations Among Tasks, Clusters, and Features for Multitask Clustering, IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no.2, pp. 355-368, 2019.
63. Zhiwen Yu, Yidong Zhang, Jane You, C. L. Philip Chen, Hau-San Wong, Guoqiang Han, Adaptive Semi-Supervised Classifier Ensemble for High Dimensional Data Classification, IEEE Transactions on Cybernetics, vol. 49, no. 2, pp. 366-379, Feb. 2019.
64. Zhiwen Yu, Daxing Wang, Zhuoxiong Zhao, C. L. Philip Chen, Jane You, Hau-San Wong, Hybrid incremental ensemble learning for noisy real-world data classification, IEEE Transactions on Cybernetics, vol. 49, no. 2, pp. 403-416, Feb. 2019.
65. Zhiwen Yu, Yidong Zhang, C. L. Philip Chen, Jane You, Hau-San Wong, Dan Dai, Si Wu, “Multiobjective semisupervised classifier ensemble”, IEEE Transactions on Cybernetics, vol. 49, no. 6, pp. 2280-2293, June 2019.
66. Yong Du, Guoqiang Han, Yuhui Quan, Zhiwen Yu, Hau-San Wong, C. L. Philip Chen, Jun Zhang, Exploiting Global Low-rank Structure and Local Sparsity Nature for Tensor Completion, IEEE Transactions on Cybernetics, vol.49, no.11, pp. 3898-3910, 2019.
67. Zhiwen Yu, Peinan Luo, Jiming Liu Hau-San Wong, Jane You, Guoqiang Han Jun Zhang, “Semi-supervised ensemble clustering based on selected constraint projection”, IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 12, pp. 2394-2407, 1 Dec. 2018.
68. Zhiwen Yu, Ye Lu, Jun Zhang,Jane You,Hau-San Wong, Yide Wang, Guoqiang Han, Progressive Semisupervised Learning of Multiple Classifiers, IEEE Transactions on Cybernetics, vol. 48, no. 2, pp. 689-702. 2018.
69. Zhiqiang Wang, Zhiwen Yu*, C. L. Philip Chen, Jane You, Tianlong Gu, Hau-San Wong, Jun Zhang, “Clustering by Local Gravitation”, IEEE Transactions on Cybernetics, vol. 48, no. 5, pp. 1383-1396, 2018.
70. Si Wu, Qiujia Ji, Shufeng Wang, Hau-San Wong, Zhiwen Yu, Yong Xu, Semi-Supervised Image Classification with Self-Paced Cross-Task Networks, IEEE Transactions on Multimedia, vol. 20, no. 4, pp. 851-865, 2018.
71. Zhiwen Yu, Zongqiang Kuang, Jiming Liu, Hongsheng Chen, Jun Zhang, Jane You, Hau-San Wong, Guoqiang Han, “Adaptive ensembling of semi-supervised clustering solutions”, IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 8, pp. 1577-1590, Aug. 1 2017.
72. Zhiwen Yu, Zhiqiang Wang, Jane You, Jun Zhang, Jiming Liu, Hau-San Wong, and Guoqiang Han, A New Kind of Nonparametric Test for Statistical Comparison of Multiple Classifiers Over Multiple Datasets, IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4418-4431, Dec. 2017.
73. Zhiwen Yu, Xianjun Zhu, Hau-San Wong, Jane You, Jun Zhang, Guoqiang Han, “Distribution based Cluster Structure Selection”, IEEE Transactions on Cybernetics, vol. 47, no. 11, pp. 3554-3567, Nov. 2017.
74. Zhiwen Yu, Peinan Luo, Jane You, Hau-San Wong, Hareton Leung, Si Wu, Jun Zhang, Guoqiang Han，Incremental Semi-supervised Clustering Ensemble for High Dimensional Data Clustering, IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 3, pp. 701-714, 2016.
75. Zhiwen Yu, Hantao Chen, Jane You, Hareton Leung, Jiming Liu, Guoqiang Han, “Hybrid K Nearest Neighbor Classifier”, IEEE Transactions on Cybernetics, vol. 46, no. 6, pp. 1263-1275, 2016.
76. Zhiwen Yu, Le Li, Jiming Liu, Jun Zhang, Guoqiang Han, Adaptive Noise Immune Cluster Ensemble Using Affinity Propagation, IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 12, pp. 3176-3189, 2015.
77. Zhiwen Yu, Le Li, Jiming Liu, Guoqiang Han, Hybrid Adaptive Classifier Ensemble, IEEE Transactions on Cybernetics, vol. 42, no. 2, pp. 177-190. 2015.
78. Zhiwen Yu, Hantao Chen, Jane You, Hau-San Wong, Jiming Liu, Guoqiang Han, Le Li, Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 3, pp. 568-582, 2015.
79. Zhiwen Yu, Hongsheng Chen, Jane You, Hau-San Wong, Jiming Liu, Le Li, Guoqiang Han, Double Selection based Semi-Supervised Clustering Ensemble for Tumor Clustering from Gene Expression Profiles, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 11, no. 4, pp. 727-740, 2014 .
80. Si Wu, Hau-San Wong, and Zhiwen Yu, A Bayesian Model for Crowd Escape Behavior Detection, IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 1, pp. 85-98, 2014.
81. Guoxian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu, “Protein Function Prediction with Incomplete Annotations”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 11, no. 3, pp. 579-591, 2014.
82. Guoxian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu, “Protein Function Prediction using Multilabel Ensemble Classification”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 4, pp. 1045-1057, 2013.
83. Zhiwen Yu, Hantao Chen, Jane You, Guoqiang Han, Le Li, Hybrid Fuzzy Cluster Ensemble Framework for Tumor Clustering from Bio-molecular Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 3, pp. 657-670, 2013.
84. Zhiwen Yu, Le Li, Jane You, Guoqiang Han, SC3: Triple spectral clustering based consensus clustering framework for class discovery from cancer gene expression profiles, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no.6, pp.1751-1765, 2012.
85. Zhiwen Yu, Jane You, Le Li, Hau-San Wong, Guoqiang Han, Representative distance: a new similarity measure for Class Discovery from Gene Expression Data, IEEE Transactions on NanoBioScience , vol.11, no.4, pp.341-351, 2012.
86. Zhiwen Yu, Hau-San Wong, Dingwen Wang, Ming Wei, “Neighborhood Knowledge-based Evolutionary Algorithm for Multiobjective Optimization Problems”, IEEE Transactions on Evolutionary Computation, Vol.15, no.6, pp. 812-831, 2011.
87. Zhiwen Yu, Hau-San Wong, Jane You, Qinmin Yang, Hongying Liao, “Knowledge based Cluster Ensemble for Cancer Discovery from Biomolecular Data”, IEEE Transactions on NanoBioScience, vol.10, no.2, pp.76-85, 2011.
88. Zhiwen Yu, Zhongkai Deng, Hau-San Wong, and Lirong Tan. “Identifying Protein Kinase-specific Phosphorylation Sites Based on the Bagging-Adaboost Ensemble Approach.” IEEE Transactions on NanoBioScience, Vol.9, no.2, pp.132-143, 2010.
89. Shaohong Zhang, Hau-San Wong, Zhiwen Yu, and Horace H.S. Ip. “Hybrid Associative Retrieval of Three-Dimensional Models”. IEEE Transactions on Systems, Man and Cybernetics -Part B: Cybernetics. Vol.40, no.6, pp.1582-1595, 2010.
90. Zhiwen Yu, Hau-San Wong. “Class Discovery from Gene Expression Data based on Perturbation and Cluster Ensemble”. IEEE Transactions on NanoBioScience, Vol.8, no.2, pp.147-160, 2009.
91. Zhiwen Yu, and Hau-San Wong. “A rule based technique for extraction of visual attention regions based on real-time clustering”. IEEE Transactions on Multimedia. vol.9, no. 4, pp. 766-784, June, 2007.
92. Hau-San Wong, Bo Ma, Zhiwen Yu, Pui Fong Yeung, and Horace H.S. Ip. “3D Head Model Retrieval Using a Single Face View Query”. IEEE Transactions on Multimedia. vol. 9, no. 5, pp. 1026-1036, 2007.
Awards：
2003 Second Prize of Wu Wenjun Artificial Intelligence Natural Science Award, 1st Author
2001 Second Prize of Natural Science Award, China Computer Federation (CCF), 1st Author
