About Me

I am a Ph.D. candidate at Monash University, supervised by Prof. Shirui Pan, Dr. Daokun Zhang, and A/Prof. Vincent Lee. I obtained my B.S. degree and M.S. degree from Beihang University in 2017 and 2020, respectively. My research interests are in graph representation learning and graph neural networks, with a special focus on unsupervised and weak-supervised scenarios. I am a recipient of the Google Ph.D. Fellowship in 2022.

News

2022/11: Our paper on graph representation learning has been accepted by AAAI 2023.
2022/11: Our paper on federated graph learning has been accepted by AAAI 2023.
2022/10: Our paper on graph OOD detection has been accepted by WSDM 2023.
2022/08: I am honoured to receive the Google Ph.D. Fellowship in 2022.
2022/05: Our survey on graph self-supervised learning has been accepted by IEEE TKDE.
2022/01: Our paper on graph structure learning has been accepted by WWW 2022.
2021/11: Our paper on dynamic graph has been accepted by IEEE TKDE.
2021/10: Our paper on graph anomaly detection has been accepted by IEEE TKDE.
2021/08: Our paper on graph anomaly detection has been accepted by CIKM 2021.
2021/06: Our paper on label propagation has been accepted by World Wide Web.
2021/03: Our paper on graph anomaly detection has been accepted by IEEE TNNLS.

Selected Papers


	Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating [PDF] [Code] Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent CS Lee, Shirui Pan. AAAI Conference on Artificial Intelligence (AAAI), 2023. [Oral presentation]
	Federated Learning on Non-IID Graphs via Structural Knowledge Sharing [PDF] [Code] Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang. AAAI Conference on Artificial Intelligence (AAAI), 2023. [Oral presentation]**
	GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection [PDF] [Code] Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan. ACM International Conference on Web Search and Data Mining (WSDM), 2023. [Oral presentation]
	Graph Self-Supervised Learning: A Survey [PDF] Yixin Liu, Ming Jin, Shirui Pan, Chuan Zhou, Yu Zheng, Feng Xia, Philip S. Yu. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
	Towards Unsupervised Deep Graph Structure Learning [PDF] [Code] Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan. The Web Conference (WWW), 2022. [Best Paper Award candidate]
	Anomaly Detection in Dynamic Graphs via Transformer [PDF] [Code] Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Qingfeng Chen, Vincent CS Lee. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.
	Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning [PDF] [Code] Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.