World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
23083
World Ranking
7352
National Ranking
233

Overview

Guodong Long is affiliated with the University of Technology Sydney in Australia and has made contributions primarily in the field of Computer Science, with a focus on Artificial Intelligence. Their research spans several subfields including Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Statistical and Nonlinear Physics.

The scientist has a broad range of research interests concentrating on topics such as Privacy-Preserving Technologies in Data, Topic Modeling, Domain Adaptation and Few-Shot Learning, Recommender Systems and Techniques, Advanced Graph Neural Networks, Time Series Analysis and Forecasting, and Natural Language Processing Techniques.

Guodong Long's recent papers include:

  • Multi-center federated learning: clients clustering for better personalization (2022), published in World Wide Web
  • FedProto: Federated Prototype Learning across Heterogeneous Clients (2022), Proceedings of the AAAI Conference on Artificial Intelligence
  • Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications (2020), IEEE Transactions on Computational Social Systems
  • Federated Learning on Non-IID Graphs via Structural Knowledge Sharing (2023), Proceedings of the AAAI Conference on Artificial Intelligence
  • Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks (2020), arXiv (Cornell University)

The scientist has collaborated frequently with other researchers including Jing Jiang, Chengqi Zhang, Tao Shen, and Tianyi Zhou.

Guodong Long regularly publishes in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • World Wide Web
  • IEEE Transactions on Neural Networks and Learning Systems

In addition to journal and conference articles, Guodong Long has authored books published by Springer Science+Business Media, including:

  • AI 2021: Advances in Artificial Intelligence (2022)
  • Advanced Data Mining and Applications (2022)

Best Publications

  • A Comprehensive Survey on Graph Neural Networks

    Zonghan Wu;Shirui Pan;Fengwen Chen;Guodong Long

  • Graph WaveNet for Deep Spatial-Temporal Graph Modeling

    Zonghan Wu;Shirui Pan;Guodong Long;Jing Jiang

  • Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

    Zonghan Wu;Shirui Pan;Guodong Long;Jing Jiang

  • Adversarially regularized graph autoencoder for graph embedding

    Shirui Pan;Ruiqi Hu;Guodong Long;Jing Jiang

  • DiSAN: Directional Self-Attention Network for RNN/CNN-free Language Understanding

    Tao Shen;Tianyi Zhou;Guodong Long;Jing Jiang

  • FedProto: Federated Prototype Learning across Heterogeneous Clients

    Unknown

  • Attributed Graph Clustering: a Deep Attentional Embedding approach

    Chun Wang;Shirui Pan;Ruiqi Hu;Guodong Long

  • MGAE: Marginalized Graph Autoencoder for Graph Clustering

    Chun Wang;Shirui Pan;Guodong Long;Xingquan Zhu

  • Conference on Neural Information Processing Systems

    L Liu;T Zhou;Guodong Long;Jing Jiang

  • Learning Graph Embedding With Adversarial Training Methods

    Shirui Pan;Ruiqi Hu;Sai-Fu Fung;Guodong Long

  • Federated Learning for Open Banking

    Guodong Long;Yue Tan;Jing Jiang;Chengqi Zhang

  • Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications

    Shaoxiong Ji;Shirui Pan;Xue Li;Erik Cambria

  • Supervised Learning for Suicidal Ideation Detection in Online User Content

    Shaoxiong Ji;Shaoxiong Ji;Celina Ping Yu;Sai-fu Fung;Shirui Pan

  • Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

    Bo Wang;Tao Shen;Guodong Long;Tianyi Zhou

  • Learning Private Neural Language Modeling with Attentive Aggregation

    Shaoxiong Ji;Shirui Pan;Guodong Long;Xue Li

  • Optimal cloud resource auto-scaling for web applications

    Jing Jiang;Jie Lu;Guangquan Zhang;Guodong Long

  • Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

    Bo Wang;Tao Shen;Guodong Long;Tianyi Zhou

  • Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling

    Tao Shen;Tianyi Zhou;Guodong Long;Jing Jiang

  • Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop

    Jing Jiang;Jie Lu;Guangquan Zhang;Guodong Long

  • Bi-directional block self-attention for fast and memory-efficient sequence modeling

    Tao Shen;Tianyi Zhou;Guodong Long;Jing Jiang

  • Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline.

    Wensi Tang;Guodong Long;Lu Liu;Tianyi Zhou

  • Multi-Center Federated Learning

    Ming Xie;Guodong Long;Tao Shen;Tianyi Zhou

Frequent Co-Authors

Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University
Shirui Pan
Shirui Pan Griffith University
Lina Yao
Lina Yao Commonwealth Scientific and Industrial Research Organisation
Xue Li
Xue Li University of Queensland
Jia Wu
Jia Wu Macquarie University
Peng Zhang
Peng Zhang Huazhong University of Science and Technology
Daxin Jiang
Daxin Jiang Microsoft (United States)
Xingquan Zhu
Xingquan Zhu Florida Atlantic University
Quan Z. Sheng
Quan Z. Sheng Macquarie University
Yi Chang
Yi Chang Jilin University

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