PhD, Associate Professor |
I am an Associate Professor at College of Infomatics and College of Engineering, Huazhong Agricultural University. I received the Ph.D. degree in Computer Science from the University of Auckland in 2023.
My research interests lie in the areas of deep learning and graph neural networks, with emphasis on the following topics:
Signed Graph Neural Networks (SGNNs) (e.g., robust SGNNs, contrastive learning, graph augmentation)
Interpretable graph neural networks (e.g., Modal regression, Out-of-Distribution Generalization)
I am recruiting Master, with high motivation of doing research on interpretable graph neural networks. If you are interested, please feel free to contact me.
Zeyu Zhang, Lu Li, Shuyan Wan, Sijie Wang, Zhiyi Wang, Zhiyuan Lu, Dong Hao, *Wanli Li. DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks. NeurIPS 2024.
Sijie Wang, Lin Ni, *Zeyu Zhang, Xiaoxuan Li, Xianda Zheng, Jiamou Liu. Multimodal Prediction of Student Performance: A Fusion of Signed Graph Neural Networks and Large Language Models. Pattern Recognition Letters 2024.
Lin Ni, Sijie Wang, *Zeyu Zhang, Xiaoxuan Li, Xianda Zheng, Paul Denny, and Jiamou Liu. Enhancing Student Performance Prediction on Learnersourced Questions with SGNN-LLM Synergy. AAAI 2024.
Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, and Yifei Wang. Contrastive Learning for Signed Bipartite Graphs. SIGIR 2023.
Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao, Zijian Zhang. RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks. WWW 2023.
Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, and Jiamou Liu. User: Unsupervised structural entropy-based robust graph neural network. AAAI 2023.
Qiqi Wang, Ruofan Wanga, Kaiqi Zhao, Robert Amora, Benjamin Liu, Xianda Zheng, Zeyu Zhang, Zijian Huang. Towards Legal Judgment Summarization: A Structure-Enhanced Approach. ECAI 2023.
Graduate course: Artificial Neural Networks and Deep Learning
Undergraduate course: Machine Learning
Conference reviewer for AAAI, ACMMM, ECAI, WWW