World's Best Scientists 2026 revealed!
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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
76
Citations
21093
World Ranking
1353
National Ranking
37

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Guangquan Zhang is affiliated with the University of Technology Sydney in Australia. Their research primarily focuses on the field of Computer Science, with a substantial number of contributions related to Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Management Science and Operations Research, and Information Systems.

The scientist's work emphasizes several main topics, including:

  • Data Stream Mining Techniques
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Multimodal Machine Learning Applications
  • Anomaly Detection Techniques and Applications
  • Machine Learning and ELM (Extreme Learning Machine)
  • Advanced Bandit Algorithms Research

Guangquan Zhang has contributed to numerous research papers, with recent publications including:

  • "Open Set Domain Adaptation: Theoretical Bound and Algorithm," published in 2020 by IEEE Transactions on Neural Networks and Learning Systems
  • "Heterogeneous Domain Adaptation: An Unsupervised Approach," published in 2020 by IEEE Transactions on Neural Networks and Learning Systems
  • "Multisource Heterogeneous Unsupervised Domain Adaptation via Fuzzy Relation Neural Networks," published in 2020 by IEEE Transactions on Fuzzy Systems
  • "Ethics and privacy of artificial intelligence: Understandings from bibliometrics," published in 2021 by Knowledge-Based Systems
  • "A Causal Dirichlet Mixture Model for Causal Inference from Observational Data," published in 2020 by ACM Transactions on Intelligent Systems and Technology

The frequent co-authors who have collaborated closely with Guangquan Zhang include Jie Lü, Zhen Fang, Anjin Liu, Feng Liu, and Junyu Xuan.

The venues where their work is often published reflect a strong presence in both journals and preprint servers. The most common publication venues include:

  • arXiv (Cornell University)
  • Neurocomputing
  • IEEE Transactions on Fuzzy Systems
  • IEEE Transactions on Cybernetics
  • IEEE Transactions on Neural Networks and Learning Systems

In addition to journal publications, Guangquan Zhang has published books through established academic publishers. Notably, a book titled Recommender Systems was published by World Scientific in 2020.

Best Publications

  • Recommender system application developments

    Jie Lu;Dianshuang Wu;Mingsong Mao;Wei Wang

  • Learning under Concept Drift: A Review

    Jie Lu;Anjin Liu;Fan Dong;Feng Gu

  • Transfer learning using computational intelligence

    Jie Lu;Vahid Behbood;Peng Hao;Hua Zuo

  • Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques

    Jie Lu;Guangquan Zhang;Da Ruan

  • A Kernel Fuzzy c-Means Clustering-Based Fuzzy Support Vector Machine Algorithm for Classification Problems With Outliers or Noises

    Xiaowei Yang;Guangquan Zhang;Jie Lu;Jun Ma

  • Multi-Objective Group Decision Making: Methods, Software and Applications with Fuzzy Set Techniques(With CD-ROM)

    Jie Lu;Guangquan Zhang;Da Ruan;Fengjie Wu

  • A Customer Churn Prediction Model in Telecom Industry Using Boosting

    Ning Lu;Hua Lin;Jie Lu;Guangquan Zhang

  • A hybrid fuzzy-based personalized recommender system for telecom products/services

    Zui Zhang;Hua Lin;Kun Liu;Dianshuang Wu

  • Operation properties and δ-equalities of complex fuzzy sets

    Guangquan Zhang;Tharam Singh Dillon;Kai-Yuan Cai;Jun Ma

  • Concept drift detection via competence models

    Ning Lu;Guangquan Zhang;Jie Lu

  • Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research

    Yi Zhang;Yi Zhang;Guangquan Zhang;Hongshu Chen;Hongshu Chen;Alan L. Porter

  • An extended Kuhn-Tucker approach for linear bilevel programming

    Chenggen Shi;Jie Lu;Guangquan Zhang

  • Optimal cloud resource auto-scaling for web applications

    Jing Jiang;Jie Lu;Guangquan Zhang;Guodong Long

  • Decider: A fuzzy multi-criteria group decision support system

    Jun Ma;Jie Lu;Guangquan Zhang

  • An Integrated Group Decision-Making Method Dealing with Fuzzy Preferences for Alternatives and Individual Judgments for Selection Criteria

    Guangquan Zhang;Jie Lu

  • Open Set Domain Adaptation: Theoretical Bound and Algorithm

    Zhen Fang;Jie Lu;Feng Liu;Junyu Xuan

  • An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks

    Mahardhika Pratama;Jie Lu;Edwin Lughofer;Guangquan Zhang

  • Multilevel decision-making

    Jie Lu;Jialin Han;Yaoguang Hu;Guangquan Zhang

  • On bilevel multi-follower decision making: General framework and solutions

    Jie Lu;Chenggen Shi;Guangquan Zhang

  • Member contribution-based group recommender system

    Wei Wang;Guangquan Zhang;Jie Lu

  • Learning Deep Kernels for Non-Parametric Two-Sample Tests

    Feng Liu;Wenkai Xu;Jie Lu;Guangquan Zhang

Frequent Co-Authors

Jie Lu
Jie Lu University of Technology Sydney
Da Ruan
Da Ruan Ghent University
Tharam S. Dillon
Tharam S. Dillon La Trobe University
Witold Pedrycz
Witold Pedrycz University of Alberta
Zheng Yan
Zheng Yan Xidian University
Alan L. Porter
Alan L. Porter Georgia Institute of Technology
Haiyan Lu
Haiyan Lu University of Technology Sydney
Tianrui Li
Tianrui Li Southwest Jiaotong University
Mahardhika Pratama
Mahardhika Pratama University of South Australia
Chin-Teng Lin
Chin-Teng Lin University of Technology Sydney

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