About me

I am currently an Associate Professor with the Department of Computer Science, Jinan University, Guangzhou, China. I received my B.S. and Ph.D. degrees in the School of Software Engineering from South China University of Technology, China, in 2013 and 2020, respectively, advised by Prof. Qingyao Wu. I was an exchange student at the Hong Kong Baptist University in April-July, 2019, advised by Prof. Michael K. Ng. I worked as a Postdoctoral Research Fellow with the Department of Mathematics, The University of Hong Kong, from 2020 to 2021, advised by Prof. Michael K. Ng.
My current research interests include (hyper)graph learning, transfer learning, and their applications.

Selected Publications

[1]. Hanrui Wu, Andy Yip, Jinyi Long, Jia Zhang, Michael K. Ng. Simplicial Complex Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 46(1), 561-575. [ESI Highly Cited Paper, CCF-A, IF: 23.6]
[2]. Hanrui Wu, Yuguang Yan, Michael K. Ng. Hypergraph Collaborative Network on Vertices and Hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, 45(3), 3245-3258. [CCF-A, IF: 23.6] [code]

Publication List

[36]. Hanrui Wu, Yanxin Wu, Nuosi Li, Jia Zhang, Yonghui Xu, Michael K. Ng, Jinyi Long. Cold-start User Recommendation via Heterogeneous Domain Adaptation. ACM Transactions on Information Systems (TOIS), 2025. [Just Accepted, CCF-A, IF: 9.1] [code]
   We demonstrate that cold-start user recommendation and heterogeneous domain adaptation share similar properties, and the cold-start user recommendation can be formulated as a heterogeneous domain adaptation problem.

[35]. Qianzhi Ye, Jia Zhang, Hanrui Wu, Tianlong Gu, CL Philip Chen, Jinyi Long. SMLE: Semi-Supervised Multi-Label Learning with Label Enhancement. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025. [Early Access, CCF-A, IF: 10.4] [code]
[34]. Jia Zhang, Siwei Liu, Hanrui Wu, Zhe Zhang, Jinyi Long. EEG Feature Selection in Emotion Recognition Using a Fuzzy Information-Theoretic Based Optimization Approach. IEEE Transactions on Fuzzy Systems (TFS), 2025. [Early Access, CCF-B, IF: 11.9]
[33]. Jia Zhang, Jinglong Fang, Siwei Liu, Dezheng Liu, Hanrui Wu, Jinyi Long. Towards Cross-Brain Computer Interface: A Prototype-Supervised Adversarial Transfer Learning Approach with Multiple Sources. IEEE Transactions on Instrumentation and Measurement (TIM), 2024, 73, 1-13. [IF: 5.6]
[32]. Yiting Li, Jia Zhang, Hanrui Wu, Guodong Du, Jinyi Long. Consistent and specific multi-view multi-label learning with correlation information. Information Sciences (INS), 2024, 121395. [CCF-B]
[31]. Hanrui Wu, Zhengyan Ma, Zhenpeng Guo, Yanxin Wu, Jia Zhang, Guoxu Zhou, Jinyi Long. Online Privacy-Preserving EEG Classification by Source-Free Transfer Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2024, 32, 3059-3070. [IF: 4.8]
[30]. Hanrui Wu, Yanxin Wu, Nuosi Li, Min Yang, Jia Zhang, Michael K. Ng, Jinyi Long. High-order Proximity and Relation Analysis for Cross-network Heterogeneous Node Classification. Machine Learning (ML), 2024, 1-26. [CCF-B, IF: 7.5] [code]
[29]. Hanrui Wu, Andy Yip, Jinyi Long, Jia Zhang, Michael K. Ng. Simplicial Complex Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 46(1), 561-575. [CCF-A, IF: 23.6]
[28]. Hanrui Wu, Qinmei Xie, Zhuliang Yu, Jia Zhang, Siwei Liu, Jinyi Long. Unsupervised Heterogeneous Domain Adaptation for EEG Classification. Journal of Neural Engineering (JNE), 2024, 21(4), 046018. [IF: 4.0]
[27]. Guangliang He, Zhen Zhang, Hanrui Wu, Sanchuan Luo, Yudong Liu. KGCNA: Knowledge Graph Collaborative Neighbor Awareness Network for Recommendation. IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2024, 8(4), 2736-2748. [corresponding author, IF: 5.3]
[26]. Yuguang Yan, Yuanlin Chen, Shibo Wang, Hanrui Wu, Ruichu Cai. Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, 38(8), 9232-9240. [CCF-A]
[25]. Hanrui Wu, Lei Tian, Yanxin Wu, Jia Zhang, Michael K. Ng, Jinyi Long. Transferable Graph Auto-Encoders for Cross-network Node Classification. Pattern Recognition (PR), 2024, 150, 110334. [CCF-B, IF: 8.0]
[24]. Guodong Du, Jia Zhang, Ning Zhang, Hanrui Wu, Peiliang Wu, Shaozi Li. Semi-supervised imbalanced multi-label classification with label propagation. Pattern Recognition (PR), 2024, 150, 110358. [ESI Highly Cited Paper, CCF-B, IF: 8.0]
[23]. Hanrui Wu, Nuosi Li, Jia Zhang, Sentao Chen, Michael K. Ng, Jinyi Long. Collaborative Contrastive Learning for Hypergraph Node Classification. Pattern Recognition (PR), 2024, 146, 109995. [CCF-B, IF: 8.0]
[22]. Michael K. Ng, Hanrui Wu, Andy, Yip. Stability and Generalization of Hypergraph Collaborative Networks. Machine Intelligence Research (MIR), 2024, 21(1), 184-196.
[21]. Hanrui Wu, Nuosi Li, Ka Ho Kwok, Xuheng Cai, Jia Zhang, Jinyi Long, Michael K. Ng. Feature Matching Machine for Cold-start Recommendation. IEEE Transactions on Services Computing (TSC), 2024, 17(1), 98-112. [CCF-A, IF: 8.1]
[20]. Hanrui Wu, Chung Wang Wong, Jia Zhang, Yuguang Yan, Dahai Yu, Jinyi Long, Michael K. Ng. Cold-start Next-item Recommendation by User-Item Matching and Auto-encoders. IEEE Transactions on Services Computing (TSC), 2023, 16(4), 2477-2489. [CCF-A, IF: 8.1] [code]
[19]. Sentao Chen, Zheng Lin, Hanrui Wu. Riemannian Representation Learning for Multi-Source Domain Adaptation. Pattern Recognition (PR), 2023, 137, 109271. [CCF-B, IF: 8.0] [code]
[18]. Zhenpeng Guo, Huixian Zheng, Hanrui Wu, Jia Zhang, Guoxu Zhou, Jinyi Long. Transferable Multi-modal Fusion in Knee Angles and Gait Phases for Their Continuous Prediction. Journal of Neural Engineering (JNE), 2023, 20(3).
[17]. Jia Zhang, Hanrui Wu, Min Jiang, Jinghua Liu, Shaozi Li, Yong Tang, Jinyi Long. Group-preserving Label-specific Feature Selection for Multi-label Learning. Expert Systems with Applications (ESWA), 2023, 213, 118861. [code]
[16]. Hanrui Wu, Yuguang Yan, Michael K. Ng. Hypergraph Collaborative Network on Vertices and Hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023, 45(3), 3245-3258. [CCF-A, IF: 23.6] [code]
   We demonstrate that the collaborative training between nodes and hyperedges layer-by-layer is effective for learning hypergraph representations. People can use our model as a backbone for feature extraction.

[15]. Hanrui Wu, Jinyi Long, Nuosi Li, Dahai Yu, Michael K. Ng. Adversarial Auto-encoder Domain Adaptation for Cold-start Recommendation with Positive and Negative Hypergraphs. ACM Transactions on Information Systems (TOIS), 2023, 41(2), 1-25. [CCF-A, IF: 5.6]
[14]. Hanrui Wu, Yuguang Yan, Guosheng Lin, Min Yang, Michael K. Ng, Qingyao Wu. Iterative Refinement for Multi-source Visual Domain Adaptation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022, 34(6), 2810-2823. [CCF-A, IF: 8.9]
[13]. Yuguang Yan, Hanrui Wu, Yuzhong Ye, Chaoyang Bi, Min Lu, Dapeng Liu, Qingyao Wu, Michael K. Ng. Transferable Feature Selection for Unsupervised Domain Adaptation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022, 34(11), 5536-5551. [CCF-A, IF: 8.9]
[12]. Hanrui Wu, Michael K. Ng. Hypergraph Convolution on Nodes-Hyperedges Network for Semi-supervised Node Classification. ACM Transactions on Knowledge Discovery from Data (TKDD), 2022, 16(4), 1-19. [CCF-B, IF: 4.3] [code]
   We propose a simple yet effective hypergraph auto-encoder model and demonstrate that both nodes and hyperedges are important for learning informative hypergraph representations. People can use our model as a backbone for feature extraction.

[11]. Hanrui Wu, Michael K. Ng. Multiple Graphs and Low-rank Embedding for Multi-source Heterogeneous Domain Adaptation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2022, 16(4), 1-25. [CCF-B, IF: 4.3]
[10]. Hanrui Wu, Qingyao Wu, Michael K. Ng. Knowledge Preserving and Distribution Alignment for Heterogeneous Domain Adaptation. ACM Transactions on Information Systems (TOIS), 2022, 40(1), 1-29. [CCF-A, IF: 5.6] [code]
[09]. Hanrui Wu, Hong Zhu, Yuguang Yan, Jiaju Wu, Yifan Zhang, Michael K. Ng. Heterogeneous Domain Adaptation by Information Capturing and Distribution Matching. IEEE Transactions on Image Processing (TIP), 2021 30, 6364-6376. [CCF-A, IF: 11.041]
[08]. Hanrui Wu, Yuguang Yan, Sentao Chen, Xiangkang Huang, Qingyao Wu, Michael K. Ng, Joint Visual and Semantic Optimization for Zero-shot Learning. Knowledge-Based Systems (KBS), 2021, 215, 106773. [code]
[07]. Hanrui Wu, Yuguang Yan, Michael K. Ng, Qingyao Wu. Domain-attention Conditional Wasserstein Distance for Multi-source Domain Adaptation. ACM Transactions on Intelligent Systems and Technology (TIST), 2020, 11(4), 1-19.
[06]. Hanrui Wu, Yuguang Yan, Yuzhong Ye, Michael K. Ng, Qingyao Wu. Geometric Knowledge Embedding for Unsupervised Domain Adaptation. Knowledge-Based Systems (KBS), 2020, 191, 105155.
[05]. Hanrui Wu, Yuguang Yan, Yuzhong Ye, Huaqing Min, Michael K. Ng, Qingyao Wu. Online Heterogeneous Transfer Learning by Knowledge Transition. ACM Transactions on Intelligent Systems and Technology (TIST), 2019, 10(3), 1-19.
[04]. Yuguang Yan, Wen Li, Hanrui Wu, Huaqing Min, Mingkui Tan, Qingyao Wu. Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation. International Joint Conference on Artificial Intelligence (IJCAI), 2018, 7, 2969-2975. [CCF-A]
[03]. Yuguang Yan, Wen Li, Michael K. Ng, Mingkui Tan, Hanrui Wu, Huaqing Min, Qingyao Wu. Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation. International Joint Conference on Artificial Intelligence (IJCAI), 2017, 3252-3258. [CCF-A]
[02]. Qingyao Wu, Xiaoming Zhou, Yuguang Yan, Hanrui Wu, Huaqing Min, Online Transfer Learning by Leveraging Multiple Source Domains. Knowledge and Information Systems (KAIS), 2017, 52(3), 687-707. [corresponding author, CCF-B, IF: 2.531]
[01]. Qingyao Wu, Hanrui Wu, Xiaoming Zhou, Mingkui Tan, Yonghui Xu, Yuguang Yan, Tianyong Hao, Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017, 29(7), 1494-1507. [co-first author, CCF-A, IF: 9.235]

Selected Grants

[1]. Cold-start Recommendation Systems based on Transfer Learning. National Natural Science Foundation of China (2023-2025), PI
[2]. Multi-source Transfer Learning and Its Applications in Brain-computer Interfaces. Young Talent Support Project of Guangzhou Association for Science and Technology (2023-2024), PI