The underlined names represent my students.

2026

Yuchen Zhu, Kuang Zhou, Haishan Ye, Guang Dai, Ivor W. Tsang. HALO: Hardness-aware bilevel-inspired contrastive graph clustering. International Journal of Approximate Reasoning, 2026: 109657.
Yuchen Zhu, Kuang Zhou, Fabio Cuzzolin. TDCC: A trustworthy deep credal clustering method for uncertain data. IEEE Transactions on Cybernetics, 2026, 56(5): 2876-2887. (CAS Q1)
Kuang Zhou, Zixin Zhang, Haomin Xu, Liang Wang and Yimin Shi. Reliability analysis based on evidential likelihood for uncertain mixed weibull distribution. IEEE Transactions on Reliability, 2026, 75: 1020-1034.
Jiahui Gao, Kuang Zhou, Yuchen Zhu, Keyu Wu. Importance ranking in complex networks via influence-aware causal node embedding. IEEE Transactions on Network Science and Engineering, 2026, 13: 6754-6771. (CAS Q1)

2025

Kuang Zhou, Jiahui Gao. Key node identification for graphs based on graph attention networks, IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2025: 4210-4215.
Kuang Zhou, Chen Yan, Yong Xu. The vulnerability of communities in complex networks: a causal perspective on dynamic retentivity. Reliability Engineering and System Safety, 2025, 262: 111171. (CAS Q1)
Kuang Zhou, Wenbo Qin, Tianyu Sun. Cross-domain fault diagnosis of rolling bearings based on trusted multisource domain adaptation. Control and Decision, 2025, 40(7): 2251-2260. (In Chinese)
Ming Jiang, Kuang Zhou, Jiahui Gao, Fode Zhang. Integrating causal representations with domain adaptation for fault diagnosis. Reliability Engineering and System Safety, 2025, 260: 110999. (CAS Q1)
Kuang Zhou, Ming Jiang, Bogdan Gabrys, Yong Xu. Learning causal representations based on a GAE embedded autoencoder. IEEE Transactions on Knowledge and Data Engineering, 2025, 37(6): 3472-3484. (CAS Q1)

Kuang Zhou, Yuchen Zhu, Mei Guo, Ming Jiang. MvWECM: Multi-view weighted evidential c-means clustering. Pattern Recognition, 2025, 159: 111108. (CAS Q1)

Kuang Zhou, Ming Jiang, Bogdan Gabrys. GeAE: GAE-embedded autoencoder based causal representation for robust domain adaptation. IEEE International Conference on Systems, Man, and Cybernetics, 2023, 3777-3782. (CCF C)
Liang Wang, Dingqi Yang, Zhiwen Yu, Qi Han, En Wang, Kuang Zhou, Bin Guo. Acceptance-aware mobile crowdsourcing worker recruitment in social networks. IEEE Transactions on Mobile Computing, 2023, 22(2):634-646.

Kuang Zhou, Mei Guo, Arnaud Martin. Evidential prototype-based clustering based on transfer learning. International Journal of Approximate Reasoning, 2022, 151: 322-343.
Zuowei Zhang, Zhunga Liu, Arnaud Martin, Kuang Zhou. BSC: Belief shift clustering. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53(3): 1748-1760.
Kuang Zhou, Ming Jiang. Causal transfer evidential clustering. International Conference on Belief Functions. Springer, Cham, 2022: 13-22.

Zuowei Zhang, Hongpeng Tian, Lingzhi Yan, Arnaud Martin, Kuang Zhou. Learning a credal classifier with optimized and adaptive multiestimation for missing data imputation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 52(7): 4092-4104.
Zuowei Zhang, Zhe Liu, Arnaud Martin, Zhunga Liu, Kuang Zhou. Dynamic evidential clustering algorithm. Knowledge-Based Systems, 2021, 213: 106643.
Kuang Zhou, Mei Guo, Arnaud Martin. Evidential clustering based on transfer learning. International Conference on Belief Functions. Springer, Cham, 2021: 56-65. (Award: Best paper)
Kuang Zhou, Mei Guo, Ming Jiang. Evidential weighted multi-view clustering. International Conference on Belief Functions. Springer, Cham, 2021: 22-32.

Kuang Zhou, Yimin Shi. Evidential estimation of an uncertain mixed exponential distribution under progressive censoring. Entropy, 2020, 22(10): 1106.
Zhunga Liu, Linqing Huang, Kuang Zhou, Thierry Denœux. Combination of transferable classification with multisource domain adaptation based on evidential reasoning. IEEE Transactions on Neural Networks and Learning Systems, 2020, 32(5): 2015-2029.

Kuang Zhou, Arnaud Martin, and Quan Pan. A belief combination rule for a large number of sources, Journal of Advances in Information Fusion, 2019, 14(1): 22-40.

Kuang Zhou, Arnaud Martin, Quan Pan, and Zhunga Liu. SELP: Semi-supervised evidential label propagation algorithm for graph data clustering. International Journal of Approximate Reasoning, 2018, 92: 139-154.
Kuang Zhou, Quan Pan and Arnaud Martin. Evidential community detection based on density peaks. International Conference on Belief Functions. Springer, 2018: 269-277.

Kuang Zhou, Arnaud Martin, and Quan Pan. Evidence combination for a large number of sources. International Conference on Information Fusion. IEEE, 2017:1-8.
Salma Ben Dhaou, Kuang Zhou, Mouloud Kharoune, Arnaud Martin, and Boutheina Ben Yaghlane. The advantage of evidential attributes in social networks. In 20th International Conference on Information Fusion, IEEE, 2017: 991–998.

Kuang Zhou, Arnaud Martin, Quan Pan, and Zhunga Liu. ECMdd: Evidential c-medoids clustering with multiple prototypes. Pattern Recognition, 2016, 60:239–257.
Kuang Zhou, Arnaud Martin, and Quan Pan. The Belief-Noisy-OR model applied to network reliability analysis. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2016, 24(06):937-960.
Kuang Zhou, Arnaud Martin, Quan Pan, and Zhunga Liu. Evidential label propagation algorithm for graphs. International Conference on Information Fusion. IEEE, 2016: 1316–1323.
Kuang Zhou, Arnaud Martin, and Quan Pan. Semi-supervised evidential label propagation algorithm for graph data. International Conference on Belief Functions. Springer, 2016: 123–133. (Award: Best student paper)

Kuang Zhou, Arnaud Martin, Quan Pan, and Zhunga Liu. Median evidential c-means algorithm and its application to community detection. Knowledge-Based Systems, 2015, 74:69–88.
Kuang Zhou, Arnaud Martin, and Quan Pan. A similarity-based community detection method with multiple prototype representation. Physica A: Statistical Mechanics and its Applications, 2015, 438:519–531.
Kuang Zhou, Arnaud Martin, Quan Pan, and Zhunga Liu. Evidential relational clustering using medoids. International Conference on Information Fusion. IEEE, 2015: 413–420.

Kuang Zhou, Arnaud Martin, and Quan Pan. Evidential communities for complex networks. In 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer, 2014: 557–566.
Kuang Zhou, Arnaud Martin, and Quan Pan. Evidential-EM algorithm applied to progressively censored observations. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer, 2014: 180–189.
Wiem Maalel, Kuang Zhou, Arnaud Martin, and Zied Elouedi. Belief hierarchical clustering. International Conference on Belief Functions, Oxford, UK. Springer, 2014: 68-76.