Ke Liang PhD Candidate PRMI Group College of Computer Science and Technology National University of Defense Technology (NUDT) Email: liangke200694@126.com     liangke200694@gmail.com Address: Deya Road, Changsha, Hunan Province, P.R. China. [GitHub][Google Scholar][DBLP][WeChat]

About Me:

Ke Liang is a PhD student in National University of Defense Technology (NUDT) advised by Prof. Xinwang Liu. Prior to joining NUDT, he was advised by Prof. Sharon Huang as a Research Support and a PhD student at College of Information Sciences and Technology in Pennsylvania State University (PSU) for 2 years from 2020. Meanwhile, he received Master of Science degree under the supervision of Prof. Gang Tan majored in Computer Science and Engneering at PSU. Before that, he got his bachelor's degree at Beihang University (BUAA). Track records for all have been proven excellent.

Research Interests: Knowledge Graph, Graph Learning, Multi-view Learning, Healthcare AI

News:

1. [2024.04] Talk on "Temporal Graph Clustering" Temporal Graph Reading Group, Online, Organized by McGill University & Mila.
2. [2024.04] One paper has been accepted by IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
3. [2024.03] One paper has been accepted by ICME 2024.
4. [2024.02] One paper has been accepted by Briefings in Bioinformatics (BIB).
5. [2024.02] One paper has been accepted by CVPR 2024.
6. [2024.02] Win the Annual Advanced Student Award of the School.
7. [2024.01] One paper has been accepted by ICLR 2024.
8. [2024.01] One paper has been accepted by IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
9. [2023.12] Two papers have been accepted by AAAI 2024.
10. [2023.10] One paper has been accepted by eLife.
11. [2023.10] Win the Best Student Paper of CCHI 2023.
12. [2023.10] Win the "first prize @ The 15th Fudan University Doctoral Academic Forum - Information Science and Technology.
13. [2023.10] Talk on "Contrastive Learning on Knowledge Graph Embedding" @ The 15th Fudan University Doctoral Academic Forum - Information Science and Technology.
14. [2023.09] Talk on "Knowledge Graph Reasoning" @ MindSpore, Huawei.
15. [2023.07] Six papers have been accepted by ACM MM 2023.
16. [2023.06] One paper has been accepted by IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
17. [2023.06] The temperal graph clustering benchmark arXiv4TGC is built and released.
18. [2023.06] One paper has been accepted by IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE).
19. [2023.05] One paper has been accepted by Briefings in Bioinformatics (BIB).
20. [2023.04] One paper has been accepted by ICML 2023.
21. [2023.04] One paper has been accepted by IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).
22. [2023.04] One paper has been accepted by SIGIR 2023.
23. [2023.01] One paper has been accepted by Pattern Analysis and Applications (PAA).
24. [2022.12] Our repository Awesome Knowledge Graph Reasoning (AKGR) is online.
25. [2022.11] Our repository Awesome Deep Graph Clustering (ADGC) is online.
26. [2022.11] One paper has been accepted by AAAI 2023.

MORE

Selected Publications (* denotes the co-first author) [Full List]

2024
AAAI		MINES: Message Intercommunication for Inductive Relation Reasoning Over Neighbor-Enhanced Subgraphs Ke Liang, Lingyuan Meng, Sihang Zhou, Wenxuan Tu, Siwei Wang, Yue Liu, Meng Liu, Long Zhao, Xiangjun Dong, Xiangjun Dong, Xinwang Liu. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024) [Paper]
AAAI		Hawkes-Enhanced Spatial-Temporal Hypergraph Contrastive Learning Based on Criminal Correlations Ke Liang, Sihang Zhou, Meng Liu, Yue Liu, Wenxuan Tu, Yi Zhang, Liming Fang, Zhe Liu, Xinwang Liu. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024) [Paper]
TNNLS		SARF: Aliasing Relation-Assisted Self-Supervised Learning for Few-shot Relation Reasoning Lingyuan Meng, Ke Liang, Bin Xiao, Sihang Zhou, Yue Liu, Meng Liu, Xihong Yang, Xinwang Liu, Jinyan Li. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS). [Paper]
TNNLS		Self-Supervised Temporal Graph Learning with Temporal and Structural Intensity Alignment Meng Liu, Ke Liang, Yawei Zhao, Wenxuan Tu, Sihang Zhou, Xinbiao Gan, Xinwang Liu, Kunlun He. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS). [Paper]
CVPR		Learn from View Correlation: An Anchor Enhancement Strategy for Multi-view Clustering Suyuan Liu, Ke Liang, Zhibin Dong, Siwei Wang, Xihong Yang, Sihang Zhou, En Zhu, Xinwang Liu. The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR 2024). [Paper]
BIB		Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data Dayu Hu, Ke Liang, Zhibin Dong, Jun Wang, Yawei Zhao, Kunlun He. Briefings in Bioinformatics (BIB). [Paper]
2023
TKDE		Knowledge Graph Contrastive Learning based on Relation-Symmetrical Structure Ke Liang, Yue Liu*, Sihang Zhou, Wenxuan Tu, Yi Wen, Xihong Yang, Xiangjun Dong, Xinwang Liu. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) [Paper]
SIGIR		Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023) [Paper]
PAA		ABSLearn: A GNN-based Framework for Aliasing and Buffer-Size Information Retrieval Ke Liang, Jim Tan*, Dongrui Zeng, Yongzhe Huang, Sharon X. Huang, Gang Tan. Pattern Analysis and Applications (PAA) [Paper]
ACM MM		TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification Meng Liu, Ke Liang*, Dayu Hu, Hao Yu, Yue Liu, Lingyuan Meng, Wenxuan Tu, Sihang Zhou, Xinwang Liu. The 31st ACM International Conference on Multimedia (ACM MM 2023) [Paper]
ACM MM		Reinforcement Graph Clustering with Unknown Cluster Number Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, Stan Z. Li. The 31st ACM International Conference on Multimedia (ACM MM 2023) [Paper]
ICML		Dink-Net: Neural Clustering on Large Graphs Yue Liu, Ke Liang, Xinwang Liu, Jun Xia, Sihang Zhou, Xihong Yang, Stan Z. Li. The 40th International Conference on Machine Learning (ICML 2023) [Paper]
eLife		Quantitative Geometry of Blood Cells Extracted from X-Ray Histotomographic Images of Whole Zebrafish Maksim A. Yakovlev, Ke Liang, Carolyn R. Zaino, Daniel J. Vanselow, Andrew L. Sugarman, Alex Y. Lin, Patrick J. La Riviere, Yuxi Zheng, Justin D. Silverman, John C. Leichty, Sharon X. Huang, Keith C. Cheng eLife. [Paper]
BIB		scDFC: A deep fusion clustering method for single-cell RNA-seq data Dayu Hu, Ke Liang, Sihang Zhou, Wenxuan Tu, Meng Liu, Xinwang Liu. Briefings in Bioinformatics (BIB) [Paper]
		Structure Guided Multi-modal Pre-trained Transformer for Knowledge Graph Reasoning Ke Liang, Sihang Zhou, Yue Liu, Lingyuan Meng, Meng Liu, Xinwang Liu. Preprint. Under Review. [Paper]
2022
		Reasoning over Different Types of Knowledge Graphs: Static, Temporal and Multi-Modal Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun. Preprint. Under Review. [Paper]
		A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application Yue Liu, Jun Xia, Sihang Zhou, Siwei Wang, Xifeng Guo, Xihong Yang, Ke Liang, Wenxuan Tu, Stan Z. Li, Xinwang Liu. Preprint. Under Review. [Paper]
2021
PSU		Inferring Aliasing and Buffer Size Relationship in C Via Graph Neural Networks Ke Liang. Master Thesis [Paper]

Academic Service: