j9九游国际站(中国)-九游会官网j9

朱永华，博士，教授，国家级青年人才（海外）。博士毕业于新西兰奥克兰大学，随后赴新加坡科技设计大学从事博士后研究。主要研究方向为机器学习、图学习、多模态人工智能与可信人工智能，重点围绕图数据表示学习、噪声鲁棒学习、多模态信息融合及大模型安全等开展研究。近年来，在AAAI、ACM MM、IJCAI等国际重要学术会议以及Information Fusion、IEEE TKDE、IEEE TNNLS、Pattern Recognition等国际重要学术期刊发表论文50余篇，其中20余篇发表于CCF-A/一区会议或期刊，以第一作者或通讯作者发表论文15篇，相关成果Google Scholar引用超过2000次。作为主要完成人获2024年度广西自然科学一等奖（3/5）。

[1] Yonghua Zhu, Lei Feng, Zhenyun Deng, Yang Chen, Robert Amor, Michael Witbrock. Robust node classification on graph data with graph and label noise. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, 38(15): 17220-17227

[2] Yonghua Zhu, Jincheng Huang, Yang Chen, Robert Amor, Michael Witbrock. A graph transformer defence against graph perturbation by a flexible-pass filter. Information Fusion, 2024, 107: 102296

[3] Yonghua Zhu, Zhenyun Deng, Yang Chen, Robert Amor, Michael Witbrock. Chain of propagation prompting for node classification. Proceedings of the 31st ACM International Conference on Multimedia (ACM MM), 2023: 3012-3020

[4] Yonghua Zhu, Xiaofeng Zhu, Wei Zheng. Robust multi-view learning via half-quadratic minimization. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018: 3278-3284

[5] Yonghua Zhu, Junbo Ma, Changan Yuan, Xiaofeng Zhu. Interpretable learning based dynamic graph convolutional networks for Alzheimer’s disease analysis. Information Fusion, 2022, 77: 53-61

[6] Yujing Liu, Zongqian Wu, Zhengyu Lu, Ci Nie, Guoqiu Wen, Yonghua Zhu*, Xiaofeng Zhu. Noisy node classification by bi-level optimization based multi-teacher distillation. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2025, 39(18): 19033-19040

[7] Yudi Huang, Ci Nie, Hongqing He, Yujie Mo, Yonghua Zhu*, Guoqiu Wen, Xiaofeng Zhu. Multiplex graph representation learning with homophily and consistency. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2025, 39(11): 11835-11842

[8] Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang. Robust feature selection on incomplete data. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018: 3191-3197

[9] Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Pengfei Zhu, Yue Gao. Unsupervised spectral feature selection with dynamic hyper-graph learning. IEEE Transactions on Knowledge and Data Engineering, 2022, 34(6): 3016-3028

[10] Rongyao Hu, Ziwen Peng, Xiaofeng Zhu, Jiangzhang Gan, Yonghua Zhu, Junbo Ma, Guorong Wu. Multi-band brain network analysis for functional neuroimaging biomarker identification. IEEE Transactions on Medical Imaging, 2021, 40(12): 3843-3855

[11] Heng Tao Shen, Yonghua Zhu, Wei Zheng, Xiaofeng Zhu. Half-quadratic minimization for unsupervised feature selection on incomplete data. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(7): 3122-3135

[12] Xiaofeng Zhu, Yonghua Zhu, Wei Zheng, Spectral rotation for deep one-step clustering, Pattern Recognition, 2020, 105: 107175