Liu, Yang
 |
PhD, |
About me
Liu Yang is an assistant professor in the Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS), ICT, CAS.
He got his PhD from Institute of Computing Technology Chinese Academy of Sciences under the supervision of Prof. Qing He, and co-supervised by Prof. Xiang Ao. Here is his Google Scholar and DBLP Page.
From Feb 2022 to Feb 2023, he was a visiting scholar in the NExT Research Centre, National University of Singapore(NUS), adviced by Prof. Chua Tat-Seng. Also, he worked with Prof. Fuli Feng and Dr. Yunshan Ma.
Previously, he received the B.S. degree in Mathematics from Nanjing University (NJU) in 2017.
Research
My research interests include
Financial Fraud Detection
Trustworthy Graph Machine Learning
Out-of-Distribution Generalization
Privacy-perserving Computing
Recent Publications
Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua and Qing He. "FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs", In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Pages 1548–1558, 2023. [Paper] [Slides] [Talk] [ACM]
Yang Liu, Xiang Ao, Fuli Feng, and Qing He. "UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs", In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), Pages 1131–1140, 2022. [Paper] [Slides] [Talk] [ACM]
Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng and Xiang Ao. "Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective", To appear in the Twelfth International Conference on Learning Representations (ICLR2024).
Kuan Li, Yang Liu, Xiang Ao, Qing He. "Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective", International Conference on Learning Representations (ICLR), 2023. [Paper] [OpenReview]
Kuan Li, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Hao Yang and Qing He. "Reliable Representations Make A Stonger Defender: Unsupervised Structure Refinement for Robust GNN", In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), Pages 925–935, 2022. [Paper] [Code] [Slides] [arXiv] [ACM]
Yang Liu, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang and Qing He. "Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection", In Proceedings of the Web Conference (WWW), 2021. [Paper] [Code] [Slides] [Talk] [ACM]
Yang Liu, Xiang Ao, Qiwei Zhong, Jinghua Feng, Jiayu Tang, and Qing He. "Alike and Unlike: Resolving Class Imbalance Problem in Financial Credit Risk Assessment", In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020. [Paper] [Slides] [Talk] [ACM]
Yang Liu, Xiang Ao, Linfeng Dong, Chao Zhang, Jin Wang, and Qing He. "Spatiotemporal Activity Modeling via Hierarchical Cross-Modal Embedding ", IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 34, no. 1, pp. 462-474, 1 Jan. 2022, doi: 10.1109/TKDE.2020.2983892. [Paper] [Poster] [IEEE]
Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Yang Hao and Qing He. "AUC-oriented Graph Neural Network for Fraud Detection", In Proceedings of the ACM Web Conference (WWW), Pages 1311–1321, 2022. [Paper] [Slides] [ACM]
Zidi Qin, Yang Liu, Qing He and Xiang Ao. "Explainable Graph-based Fraud Detection via Neural Meta-graph Search", In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), Pages 4414–4418, 2022. [Paper] [Code] [Poster] [ACM]
Linfeng Dong, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Yang Hao and Qing He. "Bi-Level Selection via Meta Gradient for Graph-based Fraud Detection", In Proceedings of the 27th International Conference on Database Systems for Advanced Applications (DASFAA), 2022. [Paper] [Slides] [Springer]
Qiwei Zhong, Yang Liu, Xiang Ao, Binbin Hu, Jinghua Feng, Jiayu Tang and Qing He. "Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information Network", In Proceedings of the Web Conference (WWW), 2020. [Paper] [Slides] [Talk] [ACM]
Xiaoqian Zhu, Xiang Ao, Zidi Qin, Yanpeng Chang, Yang Liu, Qing He, Jianping Li. "Intelligent Financial Fraud Detection Practices in Post-Pandemic Era". The Innovation, Volume 2, Issue 4, 28 November 2021, 100176. [Paper] [The Innovation] [ScienceDirect]
Service
Program Committee Member
KDD 2023, 2022
WWW 2024
IJCAI 2024
AAAI 2024, 2023, 2022
NeurIPS 2023
ICLR 2024
SDM 2024
ECML-PKDD 2023
LOG 2023
Journal Reviewer
ACM Computing Survey
IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Pattern Recognition
Neural Networks