Meng Liu is an Assistant Professor of HENU-100 Talents Program at Henan University. He received the Ph.D. degree from National University of Defense Technology supervised by Prof. Xinwang Liu, and was also a Joint Student at National University of Singapore supervised by Prof. Beng Chin OOI. His research interests include graph neural network, multi-modal, and clustering. He has published more than 30 papers including TPAMI, AdvSci, TKDE, and NeurIPS, ICML, CVPR, with 1 ESI Hot Paper, 3 ESI Highly Cited Papers, and 1600 citations. He received awards such as Best Paper of 2024 China Computational Power Conference, 2025 DAAD AInet Fellowship, Youth Outstanding Paper Shortlist of WAIC 2025, Excellent Paper of GHMIG 2025, Best Student Paper of CCHI 2023, etc. He is on the Editorial Board of Information Processing & Management, Scientific Reports, and Youth Editorial Board of Engineered Science, INSC. He also serves as Area Chair for ICLR, ICASSP, COLM, and reviewer for TPAMI, TKDE, AIJ, ICML, CVPR, ACL, etc.
[J] Meng Liu, Ke Liang, Siwei Wang, Xingchen Hu, Sihang Zhou, Xinwang Liu. Deep Temporal Graph Clustering: A Comprehensive benchmark and Datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2025. Excellent Paper (5 Papers in Conference) of GHMIG 2025.
[J] Meng Liu, Ke Liang, Miaomiao Li, Xueling Zhu, Xinwang Liu. Dictionary Multi-Modal Temporal Graph Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2026.
[C] Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu. Deep Temporal Graph Clustering. The 12th International Conference on Learning Representations (ICLR), 2025. Best Paper (10 Papers Nationwide) of 2024 China Computational Power Conference, Youth Outstanding Paper Shortlist (40 Papers Worldwide) of WAIC 2025, Excellent Poster of 2024 World Young Scientist Summit.
[J] Meng Liu, Ke Liang, Yawei Zhao, Wenxuan Tu, Sihang Zhou, Xinbiao Gan, Xinwang Liu, Kunlun He. Self-Supervised Temporal Graph Learning with Temporal and Structural Intensity Alignment. IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 2024. ESI Highly Cited Paper.
[J] Meng Liu, Ke Liang, Hao Yu, Lingyuan Meng, Siwei Wang, Sihang Zhou, Xinwang Liu. Multiview Temporal Graph Clustering. IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 2025.
2026
[J] Meng Liu, Ke Liang, Miaomiao Li, Xueling Zhu, Xinwang Liu. Dictionary Multi-Modal Temporal Graph Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI. (一区Top, IF=18.6, CCF A)
2025
[J] Hao Yu, Chuan Ma, Meng Liu, Tianyu Du, Ming Ding, Tao Xiang, Shouling Ji, Xinwang Liu. GuardFL: Safeguarding Federated Learning against Backdoor Attacks via Attributed Client Graph Clustering. IEEE Transactions on Information Forensics and Security, TIFS. (一区Top, IF=8, CCF A)
[J] Yue Liu, Ke Liang, Jun Xia, Meng Liu, Xihong Yang, Xinwang Liu, Sihang Zhou, Stan Z Li. SKIP: A Prototype-based Scalable Knowledge Graph Representation Learning Method. IEEE Transactions on Neural Networks and Learning Systems, TNNLS. (一区Top, IF=8.9, CCF B)
[C] Zeyu Zhu, Ke Liang, Lingyuan Meng, Meng Liu, Suyuan Liu, Renxiang Guan, Miaomiao Li, Wanwei Liu, Xinwang Liu. SAINT: Sequence-Aware Integration for Spatial Transcriptomics Multi-View Clustering. The 39th Annual Conference on Neural Information Processing Systems, NeurIPS 2025. (CCF A, Acceptance Rate=24.5%)
[J] Junyi Yan, Enguang Zuo, Ke Liang, Meng Liu, Miaomiao Li, Xinwang Liu, Xiaoyi Lv, Kai Lu. Address Anomalies at Critical Crossroads for Graph Anomaly Detection. IEEE Transactions on Knowledge and Data Engineering, TKDE. (一区Top, IF=10.4, CCF A, Excellent Paper of The 18th Hunan Province Postgraduate Innovation Forum)
[J] Meng Liu, Ke Liang, Siwei Wang, Xingchen Hu, Sihang Zhou, Xinwang Liu. Deep Temporal Graph Clustering: A Comprehensive benchmark and Datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI. (一区Top, IF=18.6, CCF A, Excellent Paper (5 Papers in Conference) of GHMIG 2025) [Code]
[J] Meng Liu, Ke Liang, Hao Yu, Lingyuan Meng, Siwei Wang, Sihang Zhou, Xinwang Liu. Multiview Temporal Graph Clustering. IEEE Transactions on Neural Networks and Learning Systems, TNNLS. (一区Top, IF=8.9, CCF B) [Code]
[C] Hao Yu, Weixuan Liang, Ke Liang, Suyuan Liu, Meng Liu, Xinwang Liu. On the Adversarial Robustness of Multi-Kernel Clustering. The 42nd International Conference on Machine Learning, ICML 2025. (CCF A, Acceptance Rate=26.9%)
[C] Zhibin Dong, Meng Liu, Siwei Wang, Ke Liang, Yi Zhang, Suyuan Liu, Jiaqi Jin, Xinwang Liu, En Zhu. Enhanced then Progressive Fusion with View Graph for Multi-View Clustering. The 42nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025. (CCF A, Acceptance Rate=22.1%)
[J] Meng Liu, Yong Liu, Qianqian Ren, Meng Han. Rethinking Multi-Level Information Fusion in Temporal Graphs: Pre-Training Then Distilling for Better Embedding. Information Fusion. (一区Top, IF=15.5, CAAI A, ESI Highly Cited Paper)
[J] Zhibin Dong, Pei Li, Yi Jiang, Zhihan Wang, Shihui Fu, Hebin Che, Meng Liu, Xiaojing Zhao, Chunlei Liu, Chenghui Zhao, Qin Zhong, Chongyou Rao, Siwei Wang, Suyuan Liu, Dayu Hu, Dongjin Wang, Juntao Gao, Kai Guo, Xinwang Liu, En Zhu, Kunlun He. Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks. Advanced Science. (一区Top, IF=14.3, Cover Article)
2024
[J] Lingyuan Meng, Ke Liang, Hao Yu, Yue Liu, Sihang Zhou, Meng Liu, Xinwang Liu. FedEAN: Entity-Aware Adversarial Negative Sampling for Federated Knowledge Graph Reasoning. IEEE Transactions on Knowledge and Data Engineering, TKDE. (二区, IF=8.9, CCF A)
[J] Ke Liang, Lingyuan Meng, Hao Li, Meng Liu, Siwei Wang, Sihang Zhou, Xinwang Liu, Kunlun He. MGKsite: Multi-Modal Knowledge-Driven Site Selection via Intra and Inter-Modal Graph Fusion. IEEE Transactions on Multimedia, TMM. (一区Top, IF=8.4, CCF A)
[C] Ke Liang, Lingyuan Meng, Yue Liu, Meng Liu, Wei Wei, Siwei Wang, Suyuan Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu. Simple Yet Effective: Structure Guided Pre-trained Transformer for Multi-modal Knowledge Graph Reasoning. The 32nd ACM International Conference on Multimedia, ACM MM 2024. (CCF A, Acceptance Rate=26.2%)
[J] Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun, Kunlun He. A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal. IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI. (一区Top, IF=20.8, CCF A, ESI Hot Paper, ESI Highly Cited Paper, Excellent Poster of 2025 CCF-AI China Graph Machine Learning Conference, 300+ Citations, 1400+ Stars) [Code]
[J] Meng Liu, Ke Liang, Yawei Zhao, Wenxuan Tu, Sihang Zhou, Xinbiao Gan, Xinwang Liu, Kunlun He. Self-Supervised Temporal Graph Learning with Temporal and Structural Intensity Alignment. IEEE Transactions on Neural Networks and Learning Systems, TNNLS. (一区Top, IF=10.4, CCF B, ESI Highly Cited Paper) [Code]
[C] Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu. Deep Temporal Graph Clustering. The 12th International Conference on Learning Representations, ICLR 2024. (CCF A, Acceptance Rate=31.0%, Best Paper (10 Papers Nationwide) of 2024 China Computational Power Conference, Youth Outstanding Paper Shortlist (40 Papers Worldwide) of WAIC 2025, Excellent Poster of 2024 World Young Scientist Summit) [Code]
[J] Lingyuan Meng, Ke Liang, Bin Xiao, Sihang Zhou, Yue Liu, Meng Liu, Xihong Yang, Xinwang Liu, Jinyan Li. SARF: Aliasing Relation Assisted Self-Supervised Learning for Few-shot Relation Reasoning. IEEE Transactions on Neural Networks and Learning Systems, TNNLS. (一区Top, IF=10.4, CCF B)
[C] Ke Liang, Sihang Zhou, Meng Liu, Yue Liu, Wenxuan Tu, Yi Zhang, Liming Fang, Zhe Liu, Xinwang Liu. Hawkes-enhanced Spatial-Temporal Hypergraph Contrastive Learning based on Criminal Correlations. The 38th AAAI Conference on Artificial Intelligence, AAAI 2024. (CCF A, Acceptance Rate=23.8%)
[C] Ke Liang, Lingyuan Meng, Sihang Zhou, Wenxuan Tu, Siwei Wang, Yue Liu, Meng Liu, Long Zhao, Xiangjun Dong, Xinwang Liu. MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor-Enhanced Subgraphs. The 38th AAAI Conference on Artificial Intelligence, AAAI 2024. (CCF A, Acceptance Rate=23.8%)
2023
[C] Meng Liu, Wenxuan Tu, Ke Liang, Xinwang Liu. Structural Embedding Pre-Training for Deep Temporal Graph Learning. The 2023 China Automation Congress, CAC 2023. (CAA A, Best Student Paper (2 Papers in Conference) of CCHI 2023)
[C] Meng Liu, Ke Liang, Dayu Hu, Hao Yu, Yue Liu, Lingyuan Meng, WenxuanTu, Sihang Zhou, Xinwang Liu. TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification. The 31st ACM International Conference on Multimedia, ACM MM 2023. (CCF A, Acceptance Rate=29.3%) [Code]
[C] Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, Stan Z Li. Reinforcement Graph Clustering with Unknown Cluster Number. The 31st ACM International Conference on Multimedia, ACM MM 2023. (CCF A, Acceptance Rate=29.3%)
[J] Dayu Hu, Ke Liang, Sihang Zhou, Wenxuan Tu, Meng Liu, Xinwang Liu. scDFC: A Deep Fusion Clustering Method for Single-Cell RNA-Seq Data. Briefings in Bioinformatics, BIB. (二区Top, IF=9.5, CCF B)
[C] Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu. Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023. (CCF A, Acceptance Rate=20.1%, Most Influential SIGIR Papers by Paper Digest)
[C] Meng Liu, Jiaming Wu, Yong Liu. Embedding Global and Local Influences for Dynamic Graphs. The 31st ACM International Conference on Information and Knowledge Management, CIKM 2022. (CCF B, Short Paper, Acceptance Rate=29.0%)
[C] Jiachen Ma, Yong Liu, Meng Liu, Meng Han. Curriculum Contrastive Learning for Fake News Detection. The 31st ACM International Conference on Information and Knowledge Management, CIKM 2022. (CCF B, Short Paper, Acceptance Rate=29.0%)
[C] Wei Fan, Meng Liu, Yong Liu. A Dynamic Heterogeneous Graph Perception Network with Time-Based Mini-Batch for Information Diffusion Prediction. The 27th International Conference on Database Systems for Advanced Applications, DASFAA 2022. (CCF B, Short Paper, Acceptance Rate=27.2%)
2021
[J] Meng Liu, Ziwei Quan, Jiaming Wu, Yong Liu, Meng Han. Embedding Temporal Networks Inductively via Mining Neighborhood and Community Influences. Applied Intelligence. (二区, IF=5.0, CCF C)
[C] Meng Liu, Yong Liu. Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences. The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021. (CCF A, Short Paper, Oral, Acceptance Rate=27.6%, First SIGIR Paper and First CCF Rank A Student Paper in Heilongjiang University) [Code]
