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.
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 Prof. Yunshan Ma.
Previously, he received the B.S. degree in Mathematics from Nanjing University (NJU) in 2017.
My research interest includes graph machine learnig and AI safety. I have published 20+ papers 
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🔥 News
- 2025.01.25: 🎉 One paper is accepted by DASFFA 2025
- 2025.01.20: 🎉 Two papers are accepted by WWW 2025
- 2024.12.21: 🎉 One paper is accepted by ICASSP 2025
- 2024.12.10: 🎉 One paper is accepted by AAAI 2025
📝 Publications
🎙 Graph Machine Learning
WWW 2025SPEAR: A Structure-Preserving Manipulation Method for Graph Backdoor Attacks, Yuanhao Ding, Yang Liu, Yugang Ji, Weigao Wen, Qing He and Xiang Ao.WWW 2025Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation, Junhong Lian, Xiang Ao, Xinyu Liu, Yang Liu and Qing He.AAAI 2025Dynamic Graph Learning with Static Relations for Credit Risk Assessment, Qi Yuan, Yang Liu, Yateng Tang, Xinhuan Chen, Xuehao Zheng, Qing He and Xiang Ao.DASFAA 2025OFTEN: Graph Invariant Learning via Soft Environment Inference, Yang Liu, Zikun Zhang, Xiang Ao, Lingxiang Tian, Qing He.ICASSP 2025Domain-aware Node Representation Learning for Graph Out-of-Distribution Generalization, Yi Qiao, Yang Liu, Qing He, Xiang Ao.WSDM 2025LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework, Yiran Qiao, Xiang Ao, Yang Liu, Jiarong Xu, Xiaoqian Sun and Qing He.ICLR 2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective, Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng and Xiang Ao.ICLR 2023Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective, Kuan Li, Yang Liu, Xiang Ao, Qing He.KDD 2023FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs, Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua and Qing He.KDD 2022UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs, Yang Liu, Xiang Ao, Fuli Feng, and Qing He.WWW 2021Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection, Yang Liu, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang and Qing He.Slides Talk
CIKM 2020Alike and Unlike: Resolving Class Imbalance Problem in Financial Credit Risk Assessment, Yang Liu, Xiang Ao, Qiwei Zhong, Jinghua Feng, Jiayu Tang, and Qing He. Slides Talk Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020.
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📖 Educations
- 2017.09 - 2023.06, PhD, Institute of Computing Technology Chinese Academy of Sciences, Beijing.
- 2022.02 - 2023.02, Visiting Student, National Univeristy of Singapore, Singapore.
- 2013.09 - 2017.06, Undergraduate, Nanjing University, Nanjing.