News
Oct 2024
Two paper have been accepted by WSDM 2025!
Oct 2024
Four paper have been accepted by NeurIPS 2024!
Aug 2024
Our survey paper on Deep Clustering has been accepted by ACM Computing Surveys!
Jan 2024
Two paper on Graph-based Recommender System have been accepted by WWW 2024!
Dec 2023
Our paper on Graph Domain Adaptation has been accepted by AAAI 2024!
Dec 2023
Our paper on Dynamic Graph Pre-Training has been accepted by ICDE 2024!
Sep 2023
Our benchmark paper OpenGSL has been accepted by NeurIPS 2023!
Sep 2023
Our paper on OKD for GNN has been accepted by Journal of ESWA!
Sep 2023
One paper on Graph Anomaly Detection has been accepted by ICDM 2023!
August 2023
Four paper on Graph Clustering, Life Service Recommendation, Click-Through Rate Prediction, Debiased Recommendation have been accepted by CIKM 2023!
Jan 2023
Our paper on adaptive temperature has been accepted by WWW 2023!
Sheng Zhou
Associate professor
Eagle Lab
Zheda Road, Hangzhou, China
Email: zhousheng_zju AT zju.edu.cn
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I am an associate professor at School of Software Technology, Zhejiang University (ZJU).
My research interest includes network data mining, graph machine learning and AI for accessibility.
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We currently have several openings for PhD students (2025 Fall), master students (2025 Fall) and post-doctoral positions (Anytime) on Multi-Modal Learning and Data Mining.
Currently, we are highly interested in Visual Understanding with MLLM. Please send me email if you are intersted in the positions.
Recent Research
Selected Publications (Full List)
Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding
Zhe Wang, Sheng Zhou*, Jiawei Chen, Zhen Zhang, Binbin Hu, Yan Feng, Chun Chen, Can Wang, WSDM 2025 |
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How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective
Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang, WSDM 2025 |
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NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Zhonghao Wang, Danyu Sun, Sheng Zhou*, Haobo Wang, Jiapei Fan, Longtao Huang, Jiajun Bu NeurIPS 2024 |
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Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
Meihan Liu, Zhen Zhang, Jiachen Tang, Jiajun Bu, Bingsheng He, Sheng Zhou NeurIPS 2024 |
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GC-Bench: An Open and Unified Benchmark for Graph Condensation
Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu NeurIPS 2024 |
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PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
Weiqin Yang, Jiawei Chen, Xin Xin, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang NeurIPS 2024 |
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A Comprehensive Survey on Deep Clustering: Taxonomy,
Challenges, and Future Directions
Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester ACM Computing Surveys |
Code |
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A Survey on Graph Condensation
Hongjia Xu, Liangliang Zhang, Yao Ma, Sheng Zhou*, Zhuonan Zheng, Bu Jiajun PrePrint |
Code |
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SIGformer: Sign-aware Graph Transformer for Recommendation
Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang SIGIR 2024 |
Code |
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Structure enhanced prototypical alignment for unsupervised cross-domain
node classification
Meihan Liu, Zhen Zhang, Ning Ma, Ming Gu, Haishuai Wang, Sheng Zhou*, Jiajun Bu Neural Networks |
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MMAD:Multi-modal Movie Audio Description
Xiaojun Ye, Junhao Chen, Xiang Li, Haidong Xin, Chao Li, Sheng Zhou*, Jiajun Bu COLING 2024 |
Code |
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Distributionally Robust Graph-based Recommendation
System
Bohao Wang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yang Gao, Yan Feng, Chun Chen, Can Wang WWW 2024 |
Code |
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Online Billion-Scale Recommender Systems with Macro
Graph Neural Networks
Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang WWW 2024 |
Code |
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Rethinking Propagation for Unsupervised Graph Domain
Adaptation
Meihan Liu, Zeyu Fang, Zhen Zhang, Ming Gu, Sheng Zhou*, Xin Wang, Jiajun Bu AAAI 2024 |
Code |
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CPDG: A Contrastive Pre-Training Method for Dynamic
Graph Neural Networks
Yuanchen Bei, Hao Xu, Sheng Zhou*, Huixuan Chi, Haishuai Wang, Mengdi Zhang, Zhao Li, Jiajun Bu ICDE 2024 |
Code |
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OpenGSL: A Comprehensive Benchmark for Graph
Structure Learning
Zhiyao Zhou, Sheng Zhou*, Bochao Mao, Xuanyi Zhou, Jiawei Chen Qiaoyu Tan, Daochen Zha, Can Wang, Yan Feng, Chun Chen NeurIPS 2023 |
Code |
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Online Adversarial Knwoledge Distillation for Graph Neural
Networks
Can Wang, Zhe Wang, Defang Chen, Sheng Zhou*, Yan Feng, Chun Chen ESWA 2023 |
Code |
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Reinforcement Neighborhood Selection for Unsupervised Graph
Anomaly Detection
Yuanchen Bei, Sheng Zhou*, Qiaoyu Tan, Hao Xu, Hao Chen, Zhao Li, and Jiajun Bu ICDM 2023 |
Code |
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Homophily-enhanced Structure Learning for Graph
Clustering
Ming Gu, Gaoming Yang, Sheng Zhou*, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu CIKM 2023 |
Code |
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Non-Recursive Cluster-Scale Graph Interacted Model for
Click-Through Rate Prediction
Yuanchen Bei, Hao Chen, Shengyuan Chen, Xiao Huang, Sheng Zhou* and Feiran Huang CIKM 2023 |
Code |
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DPGN: Denoising Periodic Graph Network for Life Service
Recommendation
Hao Xu, Huixuan Chi, Danyang Liu, Sheng Zhou, Mengdi Zhang CIKM 2023 |
Code |
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CDR: Conservative Doubly Robust Learning for Debiased
Recommendation
Zijie Song, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang CIKM 2023 |
Code |
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Adap-tau: Adaptively Modulating Embedding Magnitude
for Recommendation
Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He WWW 2023 |
Code |
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Unbiased Knowledge Distillation for
Recommendation
Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He WSDM 2023 |
Code |
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Hilbert Distillation for Cross-Dimensionality
Networks
Dian Qin, Haishuai Wang, Zhe Liu, Hongjia Xu, Sheng Zhou, Jiajun Bu NeurIPS 2022 |
Code |
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Learning Spatial-Preserved Skeleton Representation
for Few-Shot Action Recognition
Ning Ma, Hongyi Zhang, Xuhui Li, Sheng Zhou*, Zhen Zhang, Jun Wen, Haifeng Li, Jingjun Gu, Jiajun Bu* ECCV 2022 |
Code |
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RMGN: A Regional Mask Guided Network for Parser-free
Virtual Try-on
Chao Lin, Zhao Li, Sheng Zhou*, Shichang Hu, Jialun Zhang, Linhao Luo, Jiarun Zhang, Longtao Huang and Yuan He IJCAI 2022 |
Code |
Collaborative Knowledge Distillation for
Heterogeneous Information Network Embedding
Can Wang, Sheng Zhou*, Kang Yu, Defang Chen, Bolang Li, Yan Feng and Chun Chen WWW 2022 |
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Code |
Distilling Holistic Knowledge with Graph Neural
Networks
Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu ICCV 2021 |
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Code |
Direction-Aware User Recommendation Based on
Asymmetric Network Embedding
Sheng Zhou, Xin Wang, Martin Ester, Bolang Li, Chen Ye, Zhen Zhang, Can Wang, Jiajun Bu TOIS |
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Code |
SamWalker++: Recommendation with Informative
Sampling Strategy
Can Wang, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen TKDE |
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Code |
Efficient Medical Image Segmentation Based
on
Knowledge Distillation
Dian Qin, Jia-Jun Bu, Zhe Liu, Xin Shen, Sheng Zhou, Jing-Jun Gu, Zhi-Hua Wang, Lei Wu, Hui-Fen Dai TMI |
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Code |
DGE: Deep Generative Network Embedding Based on
Commonality and Individuality
Sheng Zhou, Xin Wang, Jiajun Bu, Martin Ester, Pinggang Yu, Jiawei Chen, Qihao Shi, Can Wang AAAI 2020 |
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Code |
Fast Adaptively Weighted Matrix Factorization for
Recommendation with Implicit Feedback
Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Jingbang Chen, Yan Feng, Chun Chen AAAI 2020 |
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Code |
Cross Multi-Type Objects Clustering in Attributed
Heterogeneous Information Network
Sheng Zhou, Jiajun Bu, Zhen Zhang, Can Wang, Lingzhou Ma, Jianfeng Zhang KBS |
HAHE: Hierarchical Attentive Heterogeneous
Information Network Embedding
Sheng Zhou, Jiajun Bu, Xin Wang, Jiawei Chen, Can Wang Arxiv 2019 |
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Code |
Samwalker: Social recommendation with informative
sampling strategy
Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen WWW 2019 |
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Code |
Prre: Personalized relation ranking embedding for
attributed networks
Sheng Zhou, Hongxia Yang, Xin Wang, Jiajun Bu, Martin Ester, Pinggang Yu, Jianwei Zhang, Can Wang CIKM 2018 |
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Code |
ANRL: Attributed Network Representation Learning via Deep Neural Networks
Zhen Zhang, Hongxia Yang, Jiajun Bu, Sheng Zhou, Pinggang Yu, Jianwei Zhang, Martin Ester, Can Wang IJCAI 2018 |
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Code |
Projects
Awards
ICDM Cup 2022 Risk Commodities Detection on Large-scale E-commerce Graphs,🏆 Winner🏆 [Solution][Code] |
CIKM Cup 2022 Federated Hetero-Task Learning, 🏆Winner🏆 [Code] |
KDD Cup 2022 Amazon Multiclass Product Classification Task, 3rd Place Amazon Product Subtitle Identification Task, 3rd Place [Solution] |
WSDM Cup 2022 Cross-Market Recommendation Challenge, 3rd Place [Solution][Code] |
Professional Services
PC Member of Conferences: Program Committee Member of ICLR (2023,2024) Program Committee Member of WWW (2023,2024) Program Committee Member of CVPR (2022,2023,2024) Program Committee Member of AAAI (2021,2022,2023,2024) Program Committee Member of NeurIPS (2023,2024) Program Committee Member of KDD (2022,2023,2024) Program Committee Member of ICCV (2023) Program Committee Member of LOG (2022,2023) Program Committee Member of WSDM (2022) Program Committee Member of ECMLPKDD (2022) Program Committee Member of ECCV (2022,2023,2024) Program Committee Member of SDM (2023) Program Committee Member of ECAI (2024) Invited Reviewer of Journals: Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE) Invited Reviewer for ACM Transactions on Information Systems (TOIS) Invited Reviewer for IEEE Transactions on Image Processing (TIP) Invited Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS) Invited Reviewer for ACM Transactions on Knowledge Discovery from Data (TKDD) Invited Reviewer for IEEE Transactions on Big Data (TBD) Invited Reviewer for Neurocomputing |
Courses
Data Mining and Application(数据挖掘与应用)
[2021] [2022] [2023] [2024] |
An Introduction to Graph Neural Network(图神经网络导论)
[2021] [2022] [2023] [2024] |
Last update: Jan, 2024. Webpage template borrows from Xiangnan He.