World's Best Scientists 2026 revealed!
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Computer Science
New Zealand
2026

D-Index & Metrics

Computer Science

D-Index
64
Citations
21021
World Ranking
2549
National Ranking
5

Research.com Recognitions

  • 2026 - Research.com Computer Science in New Zealand Leader Award
  • 2025 - Research.com Computer Science in New Zealand Leader Award

Overview

Bing Xue is affiliated with Victoria University of Wellington in New Zealand and has a primary research focus in the field of Computer Science, particularly within Artificial Intelligence. Their body of work includes contributions to subfields such as Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Molecular Biology, and Plant Science.

The scientist's research topics emphasize Evolutionary Algorithms and Applications, Metaheuristic Optimization Algorithms Research, Advanced Multi-Objective Optimization Algorithms, Machine Learning and Data Classification, Anomaly Detection Techniques and Applications, Reinforcement Learning in Robotics, and Advanced Neural Network Applications.

Xue has authored numerous papers, including notable recent publications such as:

  • Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification, 2020, IEEE Transactions on Cybernetics
  • DHGRPO: Domain-Induced, Hierarchical Group Relative Policy Optimization, 2025, arXiv (Cornell University)
  • A survey on swarm intelligence approaches to feature selection in data mining, 2020, Swarm and Evolutionary Computation
  • An Evolutionary Multitasking-Based Feature Selection Method for High-Dimensional Classification, 2020, IEEE Transactions on Cybernetics
  • A survey on feature selection approaches for clustering, 2020, Artificial Intelligence Review

Frequent collaborators in their research include Mengjie Zhang, Ying Bi, Qi Chen, Jun Zhang, and Xin Gao.

Xue's publications are commonly found in venues such as IEEE Transactions on Evolutionary Computation, arXiv (Cornell University), Proceedings of the Genetic and Evolutionary Computation Conference Companion, IEEE Transactions on Cybernetics, and IEEE Transactions on Emerging Topics in Computational Intelligence.

In addition to articles, Xue has contributed to books published by reputable publishers, including two editions of Genetic Programming with Springer Science+Business Media in 2022 and 2024, Genetic Programming for Image Classification with Springer Nature in 2021, and Meta-Scenario Computation for Social-Geographical Sustainability with Frontiers Media in 2023.

Best Publications

  • A Survey on Evolutionary Computation Approaches to Feature Selection

    Bing Xue;Mengjie Zhang;Will N. Browne;Xin Yao

  • Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach

    Bing Xue;Mengjie Zhang;Will N. Browne

  • Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification

    Yanan Sun;Bing Xue;Mengjie Zhang;Gary G. Yen

  • Evolving Deep Convolutional Neural Networks for Image Classification

    Yanan Sun;Bing Xue;Mengjie Zhang;Gary G. Yen

  • Particle swarm optimisation for feature selection in classification

    Bing Xue;Mengjie Zhang;Will N. Browne

  • A Survey on Evolutionary Neural Architecture Search.

    Yuqiao Liu;Yanan Sun;Bing Xue;Mengjie Zhang

  • Differential evolution for filter feature selection based on information theory and feature ranking

    Emrah Hancer;Emrah Hancer;Bing Xue;Mengjie Zhang

  • A survey on swarm intelligence approaches to feature selection in data mining

    Bach Hoai Nguyen;Bing Xue;Mengjie Zhang

  • Self-Adaptive Particle Swarm Optimization for Large-Scale Feature Selection in Classification

    Yu Xue;Bing Xue;Mengjie Zhang

  • Pareto front feature selection based on artificial bee colony optimization

    Emrah Hancer;Emrah Hancer;Bing Xue;Mengjie Zhang;Dervis Karaboga

  • Completely Automated CNN Architecture Design Based on Blocks

    Yanan Sun;Bing Xue;Mengjie Zhang;Gary G. Yen

  • Variable-Length Particle Swarm Optimization for Feature Selection on High-Dimensional Classification

    Binh Tran;Bing Xue;Mengjie Zhang

  • Surrogate-Assisted Evolutionary Deep Learning Using an End-to-End Random Forest-Based Performance Predictor

    Yanan Sun;Handing Wang;Bing Xue;Yaochu Jin

  • An Evolutionary Multitasking-Based Feature Selection Method for High-Dimensional Classification

    Ke Chen;Bing Xue;Mengjie Zhang;Fengyu Zhou

  • A survey on evolutionary machine learning

    Harith Al-Sahaf;Ying Bi;Qi Chen;Andrew Lensen

  • Genetic programming for feature construction and selection in classification on high-dimensional data

    Binh Tran;Bing Xue;Mengjie Zhang

  • A New Representation in PSO for Discretization-Based Feature Selection

    Binh Tran;Bing Xue;Mengjie Zhang

  • Evolving Deep Convolutional Neural Networks by Variable-Length Particle Swarm Optimization for Image Classification

    Bin Wang;Yanan Sun;Bing Xue;Mengjie Zhang

  • Binary particle swarm optimisation for feature selection: A filter based approach

    Liam Cervante;Bing Xue;Mengjie Zhang;Lin Shang

  • A survey on feature selection approaches for clustering

    Emrah Hancer;Bing Xue;Mengjie Zhang

  • A binary ABC algorithm based on advanced similarity scheme for feature selection

    Emrah Hancer;Bing Xue;Dervis Karaboga;Mengjie Zhang

  • A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification

    Yanan Sun;Bing Xue;Mengjie Zhang;Gary G. Yen

Frequent Co-Authors

Mengjie Zhang
Mengjie Zhang Victoria University of Wellington
Gary G. Yen
Gary G. Yen Oklahoma State University
Yi Mei
Yi Mei Victoria University of Wellington
Hisao Ishibuchi
Hisao Ishibuchi Southern University of Science and Technology
Dervis Karaboga
Dervis Karaboga Erciyes University
Jing Liang
Jing Liang Zhengzhou University
Yaochu Jin
Yaochu Jin Westlake University
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
Xin Yao
Xin Yao Lingnan University
Yu Xue
Yu Xue Nanjing University of Information Science and Technology

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