Liu, Yang

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PhD Candidate,
Key Lab of Intelligent Information Processing of Chinese Academy of Sciences,
Institute of Computing Technology (ICT),
Chinese Academy of Sciences (CAS),
No. 6 Kexueyuan South Rd.
Haidian Dist., Beijing, China
E-mail: liuyang17z [@] ict [DOT] ac [DOT] cn

About me

I am a PhD candidate in the Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS), ICT, CAS.

I am fortunate to be supervised by Prof. Qing He and co-supervised by Prof. Xiang Ao. Here is my Google Scholar.

From Feb 2022, I am a visiting scholar in the NExT Research Centre, National University of Singapore(NUS), adviced by Prof. Chua Tat-Seng. Also, I work with Prof. Fuli Feng and Dr. Yunshan Ma.

Previously, I received the B.S. degree in Mathematics from Nanjing University (NJU) in 2017.

Research

My research interests include

  • Financial Fraud Detection

  • Graph Representation Learning

  • Spatio-temporal Activity Modeling

Find out more.

Recent Publications

  1. 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]

  2. 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] [arXiv] [ACM]

  3. 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]

  4. 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]

  5. 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] [IEEE]

  6. 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]

  7. Zidi Qin, Yang Liu, Qing He and Xiang Ao. "Explainable Graph-based Fraud Detection via Neural Meta-graph Search", To appear in proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. [Paper]

  8. 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]

  9. 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]

  10. 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]

Full list of publications.