World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
9878
World Ranking
4878
National Ranking
145

Overview

Jia Wu is affiliated with Macquarie University in Australia and has a significant body of research within the field of Computer Science. Their work prominently engages with subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics, and Computer Networks and Communications.

The scientist's main research topics involve Advanced Graph Neural Networks, Complex Network Analysis Techniques, Recommender Systems and Techniques, Topic Modeling, Anomaly Detection Techniques and Applications, Privacy-Preserving Technologies in Data, and Misinformation and Its Impacts.

Jia Wu has authored numerous papers published in high-impact venues. Recent notable publications include:

  • A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning, 2021, IEEE Transactions on Knowledge and Data Engineering
  • A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT, 2024, International Journal of Machine Learning and Cybernetics
  • A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting, 2023, Pattern Recognition
  • A Comprehensive Survey on Automatic Knowledge Graph Construction, 2023, ACM Computing Surveys
  • eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks, 2022, ACM Transactions on Information Systems

Frequent collaborators include Jian Yang, Philip S. Yu, Shan Xue, Hao Peng, and Chuan Zhou, contributing to a consistent coauthorship network.

The scientist's works are often published in venues such as arXiv (Cornell University), IEEE Transactions on Knowledge and Data Engineering, Neural Networks, IEEE Transactions on Big Data, and IEEE Transactions on Neural Networks and Learning Systems.

Best Publications

  • Training deep neural networks on imbalanced data sets

    Shoujin Wang;Wei Liu;Jia Wu;Longbing Cao

  • Stacked Convolutional Denoising Auto-Encoders for Feature Representation

    Bo Du;Wei Xiong;Jia Wu;Lefei Zhang

  • A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

    Xiaoxiao Ma;Jia Wu;Shan Xue;Jian Yang

  • Tri-party deep network representation

    Shirui Pan;Jia Wu;Xingquan Zhu;Chengqi Zhang

  • Infrared and visible image fusion via detail preserving adversarial learning

    Jiayi Ma;Pengwei Liang;Wei Yu;Chen Chen

  • A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning

    Di Jin;Zhizhi Yu;Pengfei Jiao;Shirui Pan

  • Deep Learning for Community Detection: Progress, Challenges and Opportunities

    Fanzhen Liu;Shan Xue;Shan Xue;Jia Wu;Chuan Zhou

  • A Comprehensive Survey on Community Detection with Deep Learning.

    Xing Su;Shan Xue;Fanzhen Liu;Jia Wu

  • A Correlation-Based Feature Weighting Filter for Naive Bayes

    Liangxiao Jiang;Lungan Zhang;Chaoqun Li;Jia Wu

  • SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

    Qingyun Sun;Jianxin Li;Hao Peng;Jia Wu

  • Bag Constrained Structure Pattern Mining for Multi-Graph Classification

    Jia Wu;Xingquan Zhu;Chengqi Zhang;Philip S. Yu

  • Nonrigid Point Set Registration With Robust Transformation Learning Under Manifold Regularization

    Jiayi Ma;Jia Wu;Ji Zhao;Junjun Jiang

  • Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs.

    Qiannan Zhu;Xiaofei Zhou;Jia Wu;Jianlong Tan

  • An unsupervised parameter learning model for RVFL neural network.

    Yongshan Zhang;Jia Wu;Zhihua Cai;Bo Du

  • A Deep Framework for Cross-Domain and Cross-System Recommendations.

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • Time series feature learning with labeled and unlabeled data

    Haishuai Wang;Haishuai Wang;Haishuai Wang;Qin Zhang;Jia Wu;Shirui Pan

  • Advances in processing, mining, and learning complex data: from foundations to real-world applications

    Jia Wu;Shirui Pan;Chuan Zhou;Gang Li

  • Boosting for Multi-Graph Classification

    Jia Wu;Shirui Pan;Xingquan Zhu;Zhihua Cai

  • Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation

    Yongshan Zhang;Jia Wu;Zhihua Cai;Philip S. Yu

  • Self-adaptive attribute weighting for Naive Bayes classification

    Jia Wu;Shirui Pan;Xingquan Zhu;Zhihua Cai

  • Multi-View Fusion with Extreme Learning Machine for Clustering

    Yongshan Zhang;Jia Wu;Chuan Zhou;Zhihua Cai

  • Attribute Weighting via Differential Evolution Algorithm for Attribute Weighted Naive Bayes (WNB)

    Jia Wu;Zhihua Cai

Frequent Co-Authors

Shirui Pan
Shirui Pan Griffith University
Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University
Xingquan Zhu
Xingquan Zhu Florida Atlantic University
Bo Du
Bo Du Wuhan University
Peng Zhang
Peng Zhang Huazhong University of Science and Technology
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Zhihua Cai
Zhihua Cai China University of Geosciences, Wuhan
Guodong Long
Guodong Long University of Technology Sydney
Jianxin Li
Jianxin Li Tianjin Polytechnic University
Quan Z. Sheng
Quan Z. Sheng Macquarie University

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