Zhenyu Yang's homepage

BIOGRAPHY

Zhenyu Yang is currently a Postdoct Research Fellow working with A/Prof. Dingqi Yang at the State Key Laboratory of Internet of Things for Smart City, University of Macau. His research focuses on developing trustworthy and robust graph anomaly detection algorithms for weakly supervised and unsupervised real-world scenarios. Previously, he received his Ph.D. and Master's degrees from the School of Computing at Macquarie University under the supervision of Prof. Jia Wu and Prof. Jian Yang .

NEWS

2026/05: Our paper on Capacity-Agnostic Parameter Isolation for Continual Graph Learning has been accepted by ICML.
2026/05: Our paper on FedHPro Federated Hyper-Prototype Learning via Gradient Matching has been accepted by ICML.
2026/02: Awarded the Vice-Chancellor’s Commendation for Academic Excellence by Macquarie University.
2026/01: Our paper on Generalizable Graph-level Anomaly Detection via Prompted Anomaly Expansion and Normality Extraction has been accepted by WWW.
2026/01: Our paper on Semi-Supervised Fake News Detection with Mixture of Experts has been accepted by WWW.
2026/01: Our paper on Revisiting Graph-Level Anomaly Detection From Partially to Fully Unsupervised Learning has been accepted by WWW.
2025/12: Our paper on Learning Subgraph-Based Normality for Interpretable Graph-Level Anomaly Detection has been accepted by TIFS.
2025/10: Our paper on Learning from Graph-Graph Relationship A New Perspective On Graph-level Anomaly Detection has been accepted by TKDE.
2025/08: Awarded the KDD 2025 Travel Grant by SIGKDD.
2025/06: Our paper on Enhancing Graph Neural Networks for Out-of-distribution Graph Detection has been accepted by TNNLS.
2025/05: Our paper on Global Interpretable Graph-level Anomaly Detection via Prototype has been accepted by SIGKDD.
2024/09: Our paper on State of the Art and Potentialities of Graph-level Learning has been accepted by CSUR.
2024/05: Awarded the Digital Finance Cooperative Research Centre (DFCRC) PhD Top-Up Scholarship by DFCRC.
2023/11: Awarded the Higher Degree Research Rising Star by School of Computing, Macquarie University.
2023/02: Our paper on Minimum Entropy Principle Guided Graph Neural Networks has been accepted by WSDM.
2022/11: Our paper on Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection has been accepted by NeurIPS.
2022/01: Our paper on Low-rank and Sparse Representation Based Learning for Cancer Survivability Prediction has been accepted by Information Science.
2021/08: Awarded the International Research Training Program (iRTP) Scholarship by Macquarie Univerisity.
2021/07: Awarded the Excellence Graduates by School of Computer Science and Engineering, University of New South Wales.

PUBLICATIONS

2026

Capacity-Agnostic Parameter Isolation for Continual Graph Learning

Ye Xiao, Ruikun Li, Zhenyu Yang, Andrey Vasnev, Junbin Gao

ICML (CCF-A)

FedHPro Federated Hyper-Prototype Learning via Gradient Matching

Huan Wang, Jun Shen, Haoran Li, Zhenyu Yang, Jun Yan, Ousman Manjang, Yanlong Zhai, Di Wu, Guansong Pang

ICML (CCF-A)

Generalizable Graph-level Anomaly Detection via Prompted Anomaly Expansion and Normality Extraction

Ge Zhang, Jiapei Chen, Guohao Sun, Xiu Fang, Zhenyu Yang, Xixun Lin, Liang Yang

WWW (CCF-A)

Semi-Supervised Fake News Detection with Mixture of Experts

Zhenyu Yang, Chaoyu Yang, Wenfeng Xu, Xiuxiu Hao, Huan Wang, Ge Zhang, Xiaoxiao Ma, Jun Shen

WWW (CCF-A)

Revisiting Graph-Level Anomaly Detection From Partially to Fully Unsupervised Learning

Zhenyu Yang, Ge Zhang, Shan Xue, Xiaoxiao Ma, JiaWu, Jian Yang, Hao Peng, Amin Beheshti

WWW (CCF-A)

2025

Learning Subgraph-Based Normality for Interpretable Graph-Level Anomaly Detection

Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang, Hao Peng, Xixun Lin

TIFS (CCF-A)

Learning from Graph-Graph Relationship A New Perspective On Graph-level Anomaly Detection

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Hao Peng, Pietro Liò

TKDE (IF 10.4, CCF-A)

Enhancing Graph Neural Networks for Out-of-distribution Graph Detection

Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang

TNNLS (IF 8.9, CCF-B)

Global Interpretable Graph-level Anomaly Detection via Prototype

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Hao Peng, Quan Z. Sheng

SIGKDD (CCF-A)

2024

State of the Art and Potentialities of Graph-level Learning

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Li`o

CSUR (IF 28)

2023

Minimum Entropy Principle Guided Graph Neural Networks

Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Hao Peng, Angsheng Li, Shan Xue, Jianlin Su

WSDM (CCF-B)

2022

Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection

Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal

NeurIPS (CCF-A)

Low-rank and Sparse Representation Based Learning for Cancer Survivability Prediction

Jie Yang, Jun Ma, Khin Than Win, Junbin Gao, Zhenyu Yang

Information Science (CCF-B)

AWARDS

• Vice-Chancellor’s Commendation for Academic Excellence.

–– Macquarie University, 2026
• KDD 2025 Travel Grant.

–– SIGKDD, 2025
• Digital Finance Cooperative Research Centre (DFCRC) PhD Top-Up Scholarship.

–– DFCRC, 2024
• Higher Degree Research Rising Star.

–– School of Computing, Macquarie University, 2023
• International Research Training Program (iRTP) Scholarship.

–– Macquarie Univerisity, 2021
• Excellence Graduates.

–– School of Computer Science and Engineering, University of New South Wales, 2021