Homepage of Chuan Zhou (周川)

• The paper on Self-Supervised Graph Representation Learning has been awarded Most Influential IJCAI Paper.
• The paper on graph neural architecture search has been awarded Most Influential IJCAI Paper.
• The paper on deep learning for community detection has been awarded Most Influential IJCAI Paper.
• The Best Student Paper Award at ICDM-2021 for the paper on fraud detection.
• One paper on neural process for cold-start Recommendation is accepted by WWW-21.
• One paper on neural architecture Search is accepted by IEEE TPAMI.
• Two papers on GNNs are accepted by NeurIPS-20.
• Three papers on adversarial attacks on GNNs, semantic network representation and attributed trust network embedding are accepted by ICDM-20.
• Call For Paper: Special Issue on Deep Structure Representation and Learning for Complex Information Networks in Complexity (IF: 2.69)
• One paper on three-way decisions is accepted by International Journal of Approximate Reasoning.
• One paper on deep learning for community detection is accepted by IJCAI-PRICAI-20 Survey Track.
• Three papers on discrete embedding, graph neural architecture search and knowledge graph reasoning are accepted by IJCAI-PRICAI-20.
• One paper on domain adaptive GCN is accepted by WWW-20.
• One paper on graph smoothing splines neural networks is accepted by AAAI-20.
• 图挖掘与图神经网络研讨会于2019年11月8日在中科院数学与系统科学研究院召开.
• Three papers on adversarial embedding, adversarial GNN and heterogeneous GNN are accepted by ICDM-19.
• One paper on evolving community detection is accepted by WWWJ.
• One paper on multi-view fusion with extreme learning machine is accepted by ACM TIST.
• Two papers on network alignment and embedding are accepted by IJCAI-19.

• Research Interests: Social Computing, Graph Computing, Graph Machine Learning, and Semantic Information
• Slides of Invited Talk: Graph Convolutional Neural Networks: An Introduction
• Slides of Invited Talk: Recommendation in Social Media: An Introduction and Recent Advances
• Slides of Invited Talk: Efficient Influence Maximization in Large-scale Social Networks

[DBLP] [ResearchGate] [Google Scholar] [Semantic Scholar]

Preprints

• Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Lio: A Comprehensive Survey of Graph-level Learning. CoRR abs/2301.05860 (2023).

• Ge Zhang, Jia Wu, Jian Yang, Shan Xue, Wenbin Hu, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu Aggarwal: Graph-level Neural Networks: Current Progress and Future Directions. CoRR abs/2205.15555 (2022). [Repository]

• Shichao Zhu, Chuan Zhou, Anfeng Cheng, Shirui Pan, Shuaiqiang Wang, Dawei Yin, Bin Wang: Geometry Contrastive Learning on Heterogeneous Graphs. CoRR abs/2206.12547 (2022). [Codes and Data]

Since 2024

• Pingtao Duan, Chuan Zhou, and Yuting Liu. Dynamic Graph Representation Learning via Coupling-Process Model. Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

• Xixun Lin, Chuan Zhou, Jia Wu, Lixin Zou, Shirui Pan, Yanan Cao, Bin Wang, Shuaiqiang Wang, and Dawei Yin. Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation. Accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).

• Xixun Lin, Zhao Li, Peng Zhang, Luchen Liu, Chuan Zhou, Bin Wang, and Zhihong Tian. Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification. Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

• Zhen Liu, Wenbo Zuo, Dongning Zhang, and Chuan Zhou. Self-attention Enhanced Auto-encoder for Link Weight Prediction with Graph Compression. Accepted by IEEE Transactions on Network Science and Engineering (TNSE).

• Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, and Philip S.Yu. A Comprehensive Survey on Community Detection with Deep Learning. Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). (Highly Cited Paper, Hot Paper)

• Xuexiong Luo, Jia Wu, Jian Yang, Hongyang Chen, Zhao Li, Hao Peng, and Chuan Zhou. Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration. Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

• Xiaoou Zhang, Yang Gao, Yang Liu, Yujia Zhu, Peng Zhang, Chuan Zhou, Qingyun Liu,and Hongyang Chen. Meta Structure Search for Link Weight Prediction In Heterogeneous Graphs. Proceedings of the 49th IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP-24), Pages 5195 - 5199.

• Fengzhao Shi, Ren Li, Yanan Cao, Yanmin Shang, Lanxue Zhang, Chuan Zhou, Jia Wu, Shirui Pan: VR-GNN: Variational Relation Vector Graph Neural Network for Modeling both Homophily and Heterophily. Accepted by World Wide Web: Internet and Web Information Systems (WWWJ).

2023

• Yang Gao, Peng Zhang, Chuan Zhou, Hong Yang, Zhao Li, Yue Hu, and Philip S. Yu. HGNAS++: Efficient Architecture Search for Heterogeneous Graphs Neural Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 35(9): 9448-9461 (2023).

• He Zhang, Xingliang Yuan, Chuan Zhou, and Shirui Pan. Projective Ranking-based GNN Evasion Attacks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 35(8): 8402-8416 (2023).

• Yuchen Zhou, Yanan Cao, Yanmin Shang, Chuan Zhou, Shirui Pan, Zheng Lin, and Qian Li. Explainable Hyperbolic Temporal Point Process for User-Item Interaction Sequence Generation. ACM Transactions on Information Systems (TOIS) 41(4): 83:1-83:26 (2023).

• Yang Gao, Peng Zhang, Hong Yang, Chuan Zhou, Yue Hu, Zhihong Tian, Zhao Li, and Jingren Zhou. GraphNAS++: Distributed Architecture Search for Graph Neural Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 35(7): 6973-6987 (2023).

• Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z. Sheng, Hui Xiong, and Leman Akoglu. A Comprehensive Survey on Graph Anomaly Detection with Deep Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE) 35(12): 12012-12038 (2023). (One of 50 Popular TKDE Articles)

• Yixin Liu, Shirui Pan, Ming Jin, Chuan Zhou, Feng Xia, and Philip S. Yu. Graph Self-Supervised Learning: A Survey. IEEE Transactions on Knowledge and Data Engineering (TKDE) 35(6): 5879-5900 (2023). (Highly Cited Paper, Hot Paper, One of 50 Popular TKDE Articles)

• Qi Huang, Chuan Zhou, Jia Wu, Luchen Liu, and Bin Wang. Deep Spatial-Temporal Structure Learning for Rumor Detection on Twitter. Neural Computing and Applications (NCAA) 35(18): 12995-13005 (2023). [Codes]

• Xixun Lin, Chuan Zhou, Jia Wu, Hong Yang, Haibo Wang, Yanan Cao, and Bin Wang. Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification. Pattern Recognition. 133: 109042 (2023).

• Sanmin Liu, Shan Xue, Jia Wu, Chuan Zhou, and Jian Yang. Online Active Learning for Drifting Data Streams. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 34(1): 186-200 (2023).

• Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou and Shirui Pan. Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs. Proceedings of the ACM Web Conference 2023 (WWW-23), Pages 611-620. [Codes]

• Yang Liu, Chuan Zhou, Peng Zhang, Shuai Zhang, Xiaoou Zhang, Zhao Li, and Hongyang Chen. Decision-focused Graph Neural Networks for Graph Learning and Optimization. In Proceedings of 2023 IEEE International Conference on Data Mining (ICDM-23), Pages 1157-1162.

• Shuai Zhang, Chuan Zhou, Peng Zhang, Yang Liu, Zhao Li, and Hongyang Chen. Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences. In Proceedings of 2023 IEEE International Conference on Data Mining (ICDM-23), Pages 808-817.

• Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan. GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels. In NeurIPS-23.

• Gehang Zhang, Bowen Yu, Jiangxia Cao, Xinghua Zhang, Jiawei Sheng, Tingwen Liu, and Chuan Zhou. ID-MixGCL: Identity Mixup for Graph Contrastive Learning. In Proceedings of 2023 IEEE International Conference on Big Data (BigData-23), Pages 473-482.

• Li Zheng, Zhenpeng Li, Zhao Li, Jun Gao, and Chuan Zhou. Domain Adaptation for Anomaly Detection on Heterogeneous Graphs in E-Commerce. In Proceedings of the 45th European Conference on Information Retrieval (ECIR-23), Pages 304-318.

2022

• Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, and George Karypis. Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), VOL. 33, NO. 6, JUNE 2022, 2378-2392.

• Ge Zhang, Zhao Li, Jiaming Huang, Jia Wu, Chuan Zhou, and Jian Yang. eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks. ACM Transactions on Information Systems (TOIS) 40(3): 47:1-47:29 (2022).

• Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Chuan Zhou, Hongyang Chen, Zhao Li, and Quan Z. Sheng. Deep Graph Level Anomaly Detection with Contrastive Learning. Scientific Reports, Volume 12, Article number: 19867 (2022).

• Yuchen Zhou, Yanmin Shang, Yanan Cao, Qian Li, Chuan Zhou, and Guandong Xu. API-GNN: Attribute Preserving Oriented Interactive Graph Neural Network. World Wide Web: Internet and Web Information Systems (WWWJ) 25(1): 239-258 (2022).

• Jian Huang, Wen Ding, Jiarun Zhang, Zhao Li, Ting Shu, Pekka Kuosmanen, Guanqun Zhou, Chuan Zhou, and Gang Yu. Variational Deep Embedding Based Active Learning for Pneumonia Diagnosis. Frontiers in Neurorobotics 16, November 2022, DOI: 10.3389/fnbot.2022.1059739.

• Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, and Steffen Staab. Ultrahyperbolic Knowledge Graph Embeddings. In proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-22), Pages 2130-2139.

• Fengzhao Shi, Yanan Cao, Yanmin Shang, Yuchen Zhou, Chuan Zhou, and Jia Wu. H2-FDetector: A GNN-based Fraud Detector with Homophilic and Heterophilic Interactions. In Proceedings of the 31th International Conference on World Wide Web (WWW-22), Pages 1486-1494.

• Weizhen Dang, Haibo Wang, Shirui Pan, Pei Zhang, Chuan Zhou, Xin Chen, and Jilong Wang. Predicting Human Mobility via Graph Convolutional Dual-attentive Networks. In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM-22), Pages 192-200.

• Yongxiu Xu, Chuan Zhou, Heyan Huang, Jing Yu, and Yue Hu. Wlinker: Modeling Relational Triplet Extraction As Word Linking. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-22), Pages 6357-6361.

• Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, and Steffen Staab. Pseudo-Riemannian Graph Convolutional Networks. Accepted by NeurIPS 2022. [An early ArXiv version]

• Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, and Charu C. Aggarwal. Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. Accepted by NeurIPS 2022.

• Yuchen Zhou, Yanmin Shang, Yanan Cao, Chuan Zhou, Chuancheng Song, Fengzhao Shi, and Qian Li. Task-level Relations Modelling for Graph Meta-learning. In Proceedings of 2022 IEEE International Conference on Data Mining (ICDM-22), Pages 813-922.

• Xin Zheng, Miao Zhang, Chunyang Chen, Chaojie Li, Chuan Zhou, and Shirui Pan. Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing. In Proceedings of 2022 IEEE International Conference on Data Mining (ICDM-22), Pages 783-792.

• Fanzhen Liu, XiaoXiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, and Charu Aggarwal. DAGAD: Data Augmentation for Graph Anomaly Detection. In Proceedings of 2022 IEEE International Conference on Data Mining (ICDM-22), Pages 259-268.

2021

• Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Chuan Zhou, Zongyuan Ge, and Steven Su. One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 43, no. 9, pp. 2921-2935.

• Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, and Bin Wang. Task-adaptive Neural Process for User Cold-Start Recommendation. In Proceedings of the 30th International Conference on World Wide Web (WWW-21), Pages 1306-1316. [Codes]

• Ming Jin, Yizhen Zheng, Yuan-Fang Li, Chen Gong, Chuan Zhou, and Shirui Pan. Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Pages 1477-1483. (Most Influential IJCAI Paper)

• Chen Li, Yuhang Niu, Shanghang Zhang, Hao Peng, Chuan Zhou, and Jianxin Li. Learning Graph Attention-Aware Knowledge Graph Embedding. Neurocomputing, Volume 461, 21 October 2021, Pages 516-529.

• Hong Yang, Peng Zhang, Haishuai Wang, Chuan Zhou, Zhao Li, Li Gao, and Qingfeng Tang. Towards Embedding Information Diffusion Data for Understanding Big Dynamic Networks. Neurocomputing 466: 265-284 (2021).

• Yongxiu Xu, Heyan Huang, Chong Feng, Chuan Zhou, Jiarui Zhang, and Yue Hu. A Relation-aware Attention Neural Network for Modeling the Usage of Scientific Online Resources. In proceedings of 2021 International Joint Conference on Neural Networks (IJCNN-21), Pages 1-8.

• He Zhang, Bang Wu, Xiangwen Yang, Chuan Zhou, Shuo Wang, Xingliang Yuan, and Shirui Pan. Projective Ranking: A Transferable Evasion Attack Method on Graph Neural Networks. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM-21), Pages 4184-4192.

• Haishuai Wang, Zhao Li, Xuanwu Liu, Donghui Ding, Zehong Hu, Peng Zhang, Chuan Zhou, and Jiajun Bu. Fulfillment-Time-Aware Personalized Ranking for On-Demand Food Recommendation. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM-21), Pages 3617-3621.

• Yang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Hong Yang, Yongchao Liu, and Yue Hu. Heterogeneous Graph Neural Architecture Search. In Proceedings of the 21th IEEE International Conference on Data Mining (ICDM-21), Pages 1072-1077.

• Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, and Bin Wang. Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. In Proceedings of the 21th IEEE International Conference on Data Mining (ICDM-21), Pages 366-375. [Codes]

• Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, and Michael Sheng. FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance. In Proceedings of the 21th IEEE International Conference on Data Mining (ICDM-21), Pages 873-882. [Codes] (Best Student Paper Award)

2020

• Man Wu, Shirui Pan, Chuan Zhou, Xiaojun Chang, and Xingquan Zhu. Unsupervised Domain Adaptive Graph Convolutional Networks. In Proceedings of the 29th International Conference on World Wide Web (WWW-20), Pages 1457-1467. [Codes]

• Fanzhen Liu, Jia Wu, Shan Xue, Chuan Zhou, Jian Yang, and Quanzheng Sheng. Detecting the evolving community structure in dynamic social networks. World Wide Web: Internet and Web Information Systems (WWWJ) 23(2): 715-733 (2020). [Codes]

• Shichao Zhu, Lewei Zhou, Shirui Pan, Chuan Zhou, Guiying Yan, and Bin Wang. GSSNN: Graph Smoothing Splines Neural Networks. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), Pages 7007-7014. [Supplementary File] [Slides] [Codes]

• Lei Li, Xindong Wu, Huanhuan Chen, Chuan Zhou, Guanfeng Liu, and Yongkang Jiang. Weighted Partial Order Oriented Three-Way Decisions under Score-based Common Voting Rules. International Journal of Approximate Reasoning. 123: 41-54 (2020).

• Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, and Philip S. Yu. Deep Learning for Community Detection: Progress, Challenges and Opportunities. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Pages 4981-4897. (Most Influential IJCAI Paper)

• Hong Yang, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, and Peng Zhang. Discrete Embedding for Latent Networks. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Pages 1223-1229.

• Yang Gao, Hong Yang, Peng Zhang, Chuan Zhou, and Yue Hu. Graph Neural Architecture Search. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Pages 1403-1409. [An early ArXiv version] [Codes] (Most Influential IJCAI Paper)

• Guojia Wan, Shirui Pan, Chen Gong, Chuan Zhou, and Reza Haffari. Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-20), Pages 1403-1409.

• Xixun Lin, Chuan Zhou, Hong Yang, Jia Wu, Haibo Wang, Yanan Cao, and Bin Wang. Exploratory Adversarial Attacks on Graph Neural Networks. In Proceedings of the 20th IEEE International Conference on Data Mining (ICDM-20), Pages 1136-1141. [Codes]

• Xuexiong Luo, Jia Wu, Chuan Zhou, Xiankun zhang, and Yuan Wang. Deep Semantic Network Representation. In Proceedings of the 20th IEEE International Conference on Data Mining (ICDM-20), Pages 1154-1159. [Codes]

• Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Chuan Zhou, and Qianli Xing. AtNE-Trust: Attributed Trust Network Embedding for Trust Prediction in Online Social Networks. In Proceedings of the 20th IEEE International Conference on Data Mining (ICDM-20), Pages 601-610. [Codes]

• Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, and Jilong Wang. Graph Stochastic Neural Networks for Semi-supervised Learning. In Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-20), Pages 1-14. [Codes]

• Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, and Bin Wang. Graph Geometry Interaction Learning. In Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-20), Pages 1-11. [Codes]

2019

• Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei Li, Jianlong Tan, and Li Guo. Deep Active Learning for Anchor User Prediction. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-19), Pages 2151-2157. [Codes]

• Hong Yang, Shirui Pan, Peng Zhang, Chuan Zhou, and Ling Chen. Low-Bit Quantization for Attributed Network Representation Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-19), Pages 4047-4053. [Codes]

• Shichao Zhu, Chuan Zhou, Shirui Pan, Xingquan Zhu, and Bin Wang. Relation Structure-Aware Heterogeneous Graph Neural Network. In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-19), Pages 1534-1539. [Slides] [Codes]

• Xixun Lin, Hong Yang, Jia Wu, Chuan Zhou, and Bin Wang. Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding. In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-19), ages 429-438. [Slides] [Codes]

• Man Wu, Shirui Pan, Xingquan Zhu, Chuan Zhou, and Lei Pan. Domain-Adversarial Graph Neural Networks for Text Classification. In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-19), Pages 648-657.

• Yongshan Zhang, Jia Wu, Chuan Zhou, Zhihua Cai, Jian Yang, and Philip S. Yu. Multi-view Fusion with Extreme Learning Machine for Clustering. ACM Transactions on Intelligent Systems and Technology (TIST), Volume 10, Number 5, November 2019, Pages 53:1-53:23.

• Xin Li, Liang Yang, Yi Li, and Chuan Zhou. Deep Trajectory: a Deep Learning Approach for Mobile Advertising in Vehicular Networks. Neural Computing and Applications 31(7): 2813-2825 (2019).

• Qi Huang, Chuan Zhou, Jia Wu, Mingwen Wang, and Bin Wang. Deep Structure Learning for Rumor Detection on Twitter. In proceedings of 2019 International Joint Conference on Neural Networks (IJCNN-19), Pages 1-8. [Codes]

• Fanzhen Liu, Jia Wu, Chuan Zhou, and Jian Yang. Evolutionary Community Detection in Dynamic Social Networks. In proceedings of 2019 International Joint Conference on Neural Networks (IJCNN-19), Pages 1-7. [Codes]

• Mengyu Zheng, Chuan Zhou, Jia Wu, and Li Guo. Smooth Deep Network Embedding. In proceedings of 2019 International Joint Conference on Neural Networks (IJCNN-19), Pages 1-8.

2018

• Chun-Yi Liu, Chuan Zhou, Jia Wu, Yue Hu, and Li Guo. Social Recommendation with an Essential Preference Space. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Pages 346-353. [Slides] [Codes]

• Li Gao, Hong Yang, Chuan Zhou, Jia Wu, Shirui Pan, and Yue Hu. Active Discriminative Network Representation Learning. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Pages 2142-2148.

• Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu, and Yue Hu. Recommendation with Multi-Source Heterogeneous Information. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Pages 3378-3384.

• Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, and Jilong Wang. Deep Structure Learning for Fraud Detection. In Proceedings of the 18th IEEE International Conference on Data Mining (ICDM-18), Pages 567-576. [Codes]

• Chuan Zhou, Wei-Xue Lu, Jingzun Zhang, Lei Li, Yue Hu, and Li Guo. Early Detection of Dynamic Harmful Cascades in Large-scale Networks. Journal of Computational Science,Volume 28, September 2018, Pages 304-317.

• Lei Li, Chuan Zhou, Jianping He, Jiamiao Wang, Xin Li, and Xindong Wu. Collective Semantic Behavior Extraction in Social Networks. Journal of Computational Science, Volume 28, September 2018, Pages 236-244.

• Wen Zan, Chuan Zhou, Hong Yang, Yue Hu, and Li Guo. iWalk: Interest-Aware Random Walk for Network Embedding. In proceedings of 2018 International Joint Conference on Neural Networks (IJCNN-18), Pages 2677-2684.

• Anfeng Cheng, Chun-Yi Liu, Chuan Zhou, Jianlong Tan, and Li Guo. User Alignment via Structural Interaction and Propagation. In proceedings of 2018 International Joint Conference on Neural Networks (IJCNN-18), Pages 5427-5434.

• Mengyu Zheng, Chuan Zhou, Jia Wu, Shirui Pan, Jinqiao Shi, and Li Guo. FraudNE: a Joint Embedding Approach for Fraud Detection. In proceedings of 2018 International Joint Conference on Neural Networks (IJCNN-18), Pages 4739-4746. [Codes]

• Lei Li, Fang Zhang, Di Ma, Chuan Zhou, and Xuegang Hu. Multi-Target Core Network-based Networked Multi-label Classification. In proceedings of 2018 IEEE International Conference on Big Knowledge (ICBK-18), Pages 274-281.

• 郭莉,曹亚男,苏马婧,尚燕敏,朱宇佳,张鹏,周川. 网络空间资源测绘:概念与技术. 信息安全学报, 第3卷, 第4期, 2018年7月, 1-14.（Li Guo, Yanan Cao, Majing Su, Yanmin Shang, Yujia Zhu, Peng Zhang, and Chuan Zhou. Cyberspace Resources Surveying and Mapping: The Concepts and Technologies. Journal of Cyber Security, Vol. 3, No.4, 2018, 1-14.)

2017

• Li Gao, Jia Wu, Chuan Zhou, and Yue Hu. Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), Pages 1316-1322.

• Yongshan Zhang, Jia Wu, Chuan Zhou, and Zhihua Cai. Instance Cloned Extreme Learning Machine. Pattern Recognition 68: 52-65 (2017)

• Peng Wang, Peng Zhang, Chuan Zhou, and Zhao Li. Hierarchical Evolving Dirichlet Processes for Modeling Nonlinear Evolutionary Traces in Temporal Data. Data Mining and Knowledge Discovery, January 2017, Volume 31, Issue 1, Pages 32–64.

• Han Deng, Hongtao Xie, Wei Ma, Zhendong Mao, and Chuan Zhou. Double-Bit Quantization and Weighting for Nearest Neighbor Search. In Proceedings of the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-17), Pages 1717-1721.

• Chun-Yi Liu, Chuan Zhou, Jia Wu, Hongtao Xie, Yue Hu, and Li Guo. CPMF: A Collective Pairwise Matrix Factorization Model for Upcoming Event Recommendation. In proceedings of 2017 International Joint Conference on Neural Networks (IJCNN-17), Pages 1532-1539. (Best Student Paper Award) [Codes]

• Shun Liu, Hongtao Xie, Chuan Zhou, Zhendong Mao, Yizhi Liu, and Xingyu Gao. Uyghur Language Text Detection in Complex Background Images Using Enhanced MSERs. In Proceedings of the 23rd International Conference on Multimedia Modeling (MMM-17), Pages 490-500.

2016

• Chuan Zhou, Wei-Xue Lu, Peng Zhang, Jia Wu, Yue Hu, and Li Guo. On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Pages 79-85.

• Li Gao, Jia Wu, Hong Yang, Zhi Qiao, Chuan Zhou, and Yue Hu. Semi-Data-Driven Network Coarsening. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI 2016), Pages 1483-1489.

• Yongshan Zhang, Jia Wu, Chuan Zhou, Peng Zhang, and Zhihua Cai. Multiple-Instance Learning with Evolutionary Instance Selection. Database Systems for Advanced Applications (21st International Conference, DASFAA 2016, Proceedings, Part I), Pages 229-241.

• Li Gao, Jia Wu, Zhi Qiao, Chuan Zhou, Hong Yang, and Yue Hu. Collaborative Social Group Influence for Event Recommendation. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM-16), Pages 1941-1944.

• Yao Lu, Zhi Qiao, Chuan Zhou, Yue Hu, and Li Guo. Location-aware Friend Recommendation in Event-based Social Networks: A Bayesian Latent Factor Approach. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM-16), Pages 1957-1960.

• Wei-Xue Lu, Chuan Zhou, and Jia Wu. Big social network influence maximization via recursively estimating influence spread. Knowledge-Based Systems (KBS), Volume 113, 1 December 2016, Pages 143–154.

• Peng Wang, Peng Zhang, Chuan Zhou, Li Guo, Binxing Fang, and Tao Yang. Modeling Multi-factor Sequential User Behavior Data over Social Networks. Chinese Journal of Electronics, Vol.25, No.2, Mar.2016, 364-371.

• Wei-Xue Lu, Chuan Zhou, Jia Wu, Chun-Yi Liu, Li Gao, and Yue Hu. A Recursive Method for Big Network Influence Estimation. In proceedings of 2016 International Joint Conference on Neural Networks (IJCNN-16), Pages 4709-4714.

• Haishuai Wang, Jia Wu, Chuan Zhou, Zhenyan Ji, and Jun Wu. Mining Subcascade Features for Cascade Outbreak Prediction in Big Networks. In proceedings of 2016 International Joint Conference on Neural Networks (IJCNN-16), Pages 3942-3949.

• 乔治，周川，纪现才，曹亚男，郭莉. 基于地域特征和异构社交关系的事件推荐算法研究. 中文信息学报，第30卷，第5期，2016年9月，47-56．（Zhi Qiao, Chuan Zhou, Xiancai Ji, Yanan Cao, and Li Guo. Event Recommendation Based on Geographical Features and Heterogeneous Social Relationships. Journal of Chinese Information Processing, 2016, 30(5): 47-56.）

2015

• Chuan Zhou, Peng Zhang, Wenyu Zang, and Li Guo. On the Upper Bounds of Spread for Greedy Algorithms in Social Network Influence Maximization. IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 27, No.10, 2015, 2770-2783.

• Peng Zhang, Chuan Zhou, Peng Wang, Byron J. Gao, Xingquan Zhu, and Li Guo. E-Tree: an efficient indexing structure for ensemble models on data streams. IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 27, No.2, 2015, 461-474.

• Wei-Xue Lu, Peng Zhang, Chuan Zhou, Chunyi Li, and Li Gao. Big Network Influence Maximization: An Incremental Algorithm for Streaming Subgraph Influence Spread Estimation. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), Pages 2076-2082.

• Wenyu Zang, Peng Zhang, Chuan Zhou, and Li Guo. Locating Multiple Sources in Social Networks under the SIR Model: A Divide-and-Conquer Approach. Journal of Computational Science, Vol. 10, September 2015, Pages 278-287.

• Peng Wang, Peng Zhang, Chuan Zhou, Zhao Li, and Li Guo. Modeling Infinite Topics on Social Behavior Data with Spatio-temporal Dependence. In Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), Pages 1919-1922.

• Qipeng Yao, Chuan Zhou, Ruisheng Shi, Peng Wang, and Li Guo. Topic-aware Social Influence Minimization. In Proceedings of the 24th International Conference on World Wide Web (WWW-15) Companion, Pages 139-140.

• Wenyu Zang, Peng Zhang, Chuan Zhou, and Li Guo. Topic-aware Source Locating in Social Networks. In Proceedings of the 24th International Conference on World Wide Web (WWW-15) Companion, Pages 141-142.

• Weiwei Feng, Peng Wang, Chuan Zhou, Peng Zhang, and Li Guo. Fast Search for Distance Dependent Chinese Restaurant Processes. In Proceedings of the 24th International Conference on World Wide Web (WWW-15) Companion, Pages 33-34.

• Xiancai Ji, Mingze Xu, Peng Zhang, Chuan Zhou, Zhi Qiao, and Li Guo. Online Event Recommendation for Event-based Social Networks. In Proceedings of the 24th International Conference on World Wide Web (WWW-15) Companion, Pages 45-46.

• Peng Wang, Chuan Zhou, Peng Zhang, Weiwei Feng, Li Guo, and Binxing Fang. Evolving Chinese Restaurant Processes for Modeling Evolutionary Traces in Temporal Data. In Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-15), Pages 79-91.

• Chuan Zhou, Ruisheng Shi, Wenyu Zang, and Li Guo. Efficient Sensor Placement Optimization for Early Detection of Contagious Outbreaks in Mobile Social Networks. In Proceedings of the IEEE 4th International Conference on Mobile Services (IEEE MS 2015), Pages 261-268.

2014

• Zhi Qiao, Peng Zhang, Wenjia Niu, Chuan Zhou, Peng Wang, and Li Guo. Online Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction. In Proceedings of the 14th IEEE International Conference on Data Mining (ICDM-14), Pages 520-529.

• Zhi Qiao, Peng Zhang, Yanan Cao, Chuan Zhou, Li Guo, and Binxing Fang. Combining Heterogenous Social and Geographical Information for Event Recommendation. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), Pages 145-151.

• Zhi Qiao, Peng Zhang, Chuan Zhou, Yanan Cao, and Li Guo. Event Recommendation in Event-based Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), Pages 3130-3131.

• Chuan Zhou, Peng Zhang, Jing Guo, and Li Guo. An Upper Bound based Greedy Algorithm for Mining Top-k Influential Nodes in Social Networks. In Proceedings of the 23rd International Conference on World Wide Web (WWW-14) Companion, Pages 421-422.

• Chuan Zhou, Peng Zhang, Wenyu Zang, and Li Guo. Maximizing the Long-term Integral Influence in Social Networks Under the Voter Model. In Proceedings of the 23rd International Conference on World Wide Web (WWW-14) Companion, Pages 423-424.

• Zhi Qiao, Peng Zhang, Jing He, Yanan Cao, Chuan Zhou, and Li Guo. Combining Geographical Information of Users and Content of Items for Accurate Rating Prediction. In Proceedings of the 23rd International Conference on World Wide Web (WWW-14) Companion, Pages 361-362.

• Wenyu Zang, Peng Zhang, Chuan Zhou, and Li Guo. Comparative Study between Incremental and Ensemble Learning on data streams: Case study. Journal of Big Data 2014 1:5.

• Chuan Zhou, Peng Zhang, Wenyu Zang, and Li Guo. Maximizing the Cumulative Influence through a Social Network when Repeat Activation Exists. Procedia Computer Science (The 14th International Conference on Computational Science (ICCS-14), Volume 29, 2014, Pages 422–431.

• Wenyu Zang, Peng Zhang, Chuan Zhou, and Li Guo. Discovering Multiple Diffusion Source Nodes in Social Networks. Procedia Computer Science (The 14th International Conference on Computational Science (ICCS-14), Volume 29, 2014, Pages 443–452. (Best Main Track Paper Award)

• Zhi Qiao, Peng Zhang, Yanan Cao, Chuan Zhou, and Li Guo. Improving Collaborative Recommendation via Location-based User-Item Subgroup. Procedia Computer Science (The 14th International Conference on Computational Science (ICCS-14), Volume 29, 2014, Pages 400–409.

• Chuan Zhou and Li Guo. A Note on Influence Maximization in Social Networks from Local to Global and Beyond. Procedia Computer Science (The 1th International Conference on Data Science (ICDS-14)), Volume 30, 2014, Pages 81-87.

• 郭静，张鹏，方滨兴，周川，曹亚男，郭莉. 基于LT模型的个性化关键传播用户挖掘.计算机学报，第37卷，第4期，2014年4月，809-818.（Jing Guo, Peng Zhang, Binxing Fang, Chuan Zhou, Yanan Cao, and Li Guo. Personalized key propagating users mining based on LT model. Chinese Journal of Computers, Vol. 37, No. 4, Apr. 2014, 809-818.）

• 郭静，曹亚男，周川，张鹏，郭莉. 基于线性阈值模型的影响力传播权重学习.电子与信息学报，第36卷，第8期，2014年8月，1804-1809.（Jing Guo, Yanan Cao, Chuan Zhou, Peng Zhang, and Li Guo. Influence weights learning under linear threshold model in social networks. Journal of Electronics and Information Technology, Vol. 36, No. 8, Aug. 2014, 1804-1809.）

• Wenyu Zang, Chuan Zhou, Xiao Wang, and Li Guo. TopicBlock: Mining User Inner Interests for Text and Link Analysis in Social Networks. In Proceedings of the 15th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT-14), Pages 159-165.

• Qipeng Yao, Chuan Zhou, Linbo Xiang, Yanan Cao, and Li Guo. Minimizing the Negative Influence By Blocking Links in Social Networks. Trustworthy Computing and Services (International Conference, ISCTCS 2014), Series Volume 520, Pages 65-73.

• Weiwei Feng, Peng Wang, Chuan Zhou, Yue Hu, and Li Guo. Nonparametric Topic-aware Sparsification of Influence Networks. Trustworthy Computing and Services (International Conference, ISCTCS 2014), Series Volume 520, Pages 83-90.

2013 and before

• Chuan Zhou, Peng Zhang, Jing Guo, Xingquan Zhu, and Li Guo. UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks. In Proceedings of the 13th IEEE International Conference on Data Mining (ICDM-13), Pages 907-916.

• Jing Guo, Peng Zhang, Chuan Zhou, Yanan Cao, and Li Guo. Personalized Influence Maximization on Social Networks. In Proceedings of the 22nd International Conference on Information and Knowledge Management (CIKM-13), Pages 199-208.

• Jing Guo, Peng Zhang, Chuan Zhou, Yanan Cao, and Li Guo. Item-based Top-K Influential Users Discovering in Social Networks. In Proceedings of the 2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW-13), Pages 780-787.

• Yuting Liu, Zhi-Ming Ma, and Chuan Zhou. Further Study on Web Markov Skeleton Processes. In: Interdisciplinary Mathematical Sciences: Volume 13, Stochastic Analysis and Applications to Finance, Essays in Honour of Jia-an Yan (2012), 313-339.

• Yuting. Liu, Zhi-Ming Ma, and Chuan Zhou. Web Markov Skeleton Processes and Their Applications. Tohoku Math. J(2) Volume 63, Number 4, Dec. 2011, 665-695.

Education

• September 2004 - July 2008, B.E. in Mathematics, School of Mathematics, Sichuan University, Chengdu, China
• September 2008 - July 2013, Ph.D in Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

Work Experience

• July 2013 - June 2015, Postdoctoral Fellow, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
• June 2015 - October 2015, Assistant Professor, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
• October 2015 - June 2019, Associate Professor, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
• June 2019 - Now, Associate Professor, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

Research Funding

• Network Embedding based Graph Anomaly Detection Model, National Natural Science Funds of China (No.61872360), 650,000 CNY, 01/01/2019-12/31/2022, Principal Investigator. (国家自然科学基金面上项目，项目负责人，已结题)

• Anomaly Detection in Social network Cascade Data Streams, National Natural Science Funds of China (No.61502479), 200,000 CNY, 01/01/2016-12/31/2018, Principal Investigator. (国家自然科学基金青年科学基金项目，项目负责人，已结题)

• Analysis and Traceability of Abnormal Information, Subproject of National Key R&D Program (No.2016YFB0801003), 757,200 CNY, 12/01/2016-11/30/2020, Principal Investigator.(国家重点研发计划，子课题负责人，已结题)

• Coordinate System and Multi-scale Subdivision Method for Cyberspace, Subproject of National Key R&D Program (No.2016YFB0801301), 880,000 CNY, 12/01/2016-11/30/2019, Principal Investigator. (国家重点研发计划，子课题负责人，已结题)

• Multidimensional Analysis and Mining of Network Public Nuisance Behavior. A Task from a National Key R&D Program (No. 2021YFB3100600), 650,000 CNY, 12/01/2021-11/30/2024, Principal Investigator. (国家重点研发计划，研究任务负责人，在研)

• Fundamentals of Mathematics for 6G Communication Network and Technology. Chinese Academy of Sciences (No. YSBR-008), 06/2021-06/2026, Key Team Member. (中国科学院稳定支持基础研究领域青年团队计划，团队主要成员，在研)

Selected Awards and Honors

• Postgraduate Excellent Course, Social Computing and Social Network Analysis, 2022 (中国科学院大学2022年学院级“研究生优秀课程”)
• Best Student Paper Award, The 21th IEEE International Conference on Data Mining, Auckland, New Zealand, 2021 (第21届数据挖掘国际会议最佳学生论文奖)
• Jingrun Chen Future Star, Academy of Mathematics and Systems Sciences, CAS, 2019 (中科院数学院陈景润未来之星)
• CCF Senior Member, 2018 (中国计算机学会高级会员)
• Best Student Paper Award, The 30th International Joint Conference on Neural Networks, Alaska, USA, 2017 (第30届神经网络国际联合会议最佳学生论文奖)
• Member of Youth Innovation Promotion Association, Chinese Academy of Sciences, 2016 (中科院青年创新促进会会员)
• Outstanding Young Talents, Institute of Information Engineering, CAS, 2015 (中科院信工所引进优秀青年人才)
• Best Paper Award, The 14th International Conference on Computational Science, Cairns, Australia, 2014 (第14届计算科学国际会议最佳论文奖)
• Outstanding Doctoral Dissertation, Chinese Academy of Sciences, 2014 (中科院优秀博士学位论文奖)

Professional Services

• 中国工业与应用数学学会(CSIAM)信息和通讯技术领域的数学专业委员会，秘书长
• 人工智能青年科学家俱乐部(青源会)，会员
• 中国指挥与控制学会信息融合专业委员会，委员
• 中国中文信息学会社会媒体处理专业委员会，委员
• 中国中文信息学会青年工作委员会，委员
• Conference SPC/PC member: NeurIPS, AAAI, KDD, IJCAI, ICDM, SDM, WWW, etc.