中文
张文熠，男，2026年6月毕业于浙江工业大学计算机科学与技术学院，获工学博士学位，师从孔祥杰教授。主要从事联邦学习、移动计算、人机交互等方向研究。作为主要成员参与多项国家自然科学基金项目。近年来，在 IEEE Transactions on Mobile Computing（TMC）、IEEE Transactions on Neural Networks and Learning Systems（TNNLS）、IEEE Transactions on Consumer Electronics（TCE）、Information Sciences 等国内外重要学术期刊发表高水平论文多篇。受邀担任 IEEE TNNLS、ACM Transactions on Intelligent Systems and Technology（TIST）、Knowledge-Based Systems（KBS）等期刊以及 AAAI、WWW 等国际会议审稿人。
主要论文：
[1] Wenyi Zhang, X. Kong, J. Xie, G. Shen, S. Yu, X. Yan. Virtual class learning for federated semi-supervised learning with open-set data. Information Sciences, 2026, 760: 124113. （CCF-B，IF=6.0）
[2] Wenyi Zhang, X. Kong, J. Xie, X. Guo, G. Shen, F. Xia. Federated learning under limited and imperfect label supervision: A survey. Expert Systems with Applications, 2026, in proof. （中科院一区Top，IF=9.4）
[3] Wenyi Zhang, X. Kong, G. Shen, Z. Wu, Y. Qu. Federated adaptive pseudo-labeling selection for semi-supervised air writing recognition systems. IEEE Transactions on Consumer Electronics, 2025, 71(2): 5856–5865. （中科院二区，IF=9.9）
[4] X. Kong, Wenyi Zhang, H. Wang, M. Hou, X. Chen, X. Yan, S. K. Das. Federated graph anomaly detection via contrastive self-supervised learning. IEEE Transactions on Neural Networks and Learning Systems, 2025, 36(5): 7931–7944. （CCF-B，IF=9.7）
[5] X. Kong, Wenyi Zhang, Y. Qu, X. Yao. FedAWR: An interactive federated active learning framework for air writing recognition. IEEE Transactions on Mobile Computing, 2024, 23(5): 6423–6436. （CCF-A，IF=8.8）
[6] Y. Zhang, G. Shen, Wenyi Zhang, K. Ning, R. Jiang, X. Kong. Uncertainty-aware traffic accident risk prediction via multi-view hypergraph contrastive learning. Information Fusion, 2025, 124: 103331. （中科院一区Top，IF=17.4）
[7] G. Shen, W. Zhou, Wenyi Zhang, N. Liu, Z. Liu, X. Kong. Bidirectional spatial–temporal traffic data imputation via graph attention recurrent neural network. Neurocomputing, 2023, 531: 151–162. （中科院二区，IF=6.7）
[8] X. Kong, W. Zhou, G. Shen, Wenyi Zhang, N. Liu, Y. Yang. Dynamic graph convolutional recurrent imputation network for spatiotemporal traffic missing data. Knowledge-Based Systems, 2023, 261: 110188. （中科院一区Top，IF=8.0）