World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
18774
World Ranking
6297
National Ranking
197

Overview

A. K. Qin is affiliated with Swinburne University of Technology in Australia and has contributed extensively to the fields of computer science and engineering, with a strong focus on artificial intelligence and related subfields. Their research output includes work on privacy-preserving technologies, remote-sensing image classification, and optimization algorithms.

The scientist's primary fields of study include:

  • Computer Science
  • Engineering

The subfields A. K. Qin has focused on cover:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Media Technology
  • Atmospheric Science
  • Computer Networks and Communications

Main topics of their research work include:

  • Privacy-Preserving Technologies in Data
  • Remote-Sensing Image Classification
  • Metaheuristic Optimization Algorithms Research
  • Advanced Multi-Objective Optimization Algorithms
  • Stochastic Gradient Optimization Techniques
  • Evolutionary Algorithms and Applications
  • Advanced Graph Neural Networks

Recent significant papers authored or co-authored by A. K. Qin include:

  • "A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges" (2020), published in IEEE Transactions on Knowledge and Data Engineering
  • "Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images" (2021), published in IEEE Transactions on Neural Networks and Learning Systems
  • "A Survey on Differentially Private Machine Learning [Review Article]" (2020), published in IEEE Computational Intelligence Magazine
  • "Evolutionary Multiform Optimization With Two-Stage Bidirectional Knowledge Transfer Strategy for Point Cloud Registration" (2022), published in IEEE Transactions on Evolutionary Computation
  • "AdvDrop: Adversarial Attack to DNNs by Dropping Information" (2021), published in 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Frequent co-authors of A. K. Qin include:

  • Maoguo Gong
  • Hao Li
  • Yue Wu
  • Yu Xie
  • Lining Xing

A. K. Qin publishes regularly in several research venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Circuits and Systems for Video Technology

Best Publications

  • Comprehensive learning particle swarm optimizer for global optimization of multimodal functions

    J.J. Liang;A.K. Qin;P.N. Suganthan;S. Baskar

  • Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization

    A.K. Qin;V.L. Huang;P.N. Suganthan

  • Self-adaptive differential evolution algorithm for numerical optimization

    A.K. Qin;P.N. Suganthan

  • Rapid and brief communication: Evolutionary extreme learning machine

    Qin-Yu Zhu;A. K. Qin;P. N. Suganthan;Guang-Bin Huang

  • Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics

    Chong Zhang;Pin Lim;A. K. Qin;Kay Chen Tan

  • Evolutionary Multitasking via Explicit Autoencoding

    Liang Feng;Lei Zhou;Jinghui Zhong;Abhishek Gupta

  • A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges

    David Alexander Tedjopurnomo;Zhifeng Bao;Baihua Zheng;Farhana Choudhury

  • Self-adaptive Differential Evolution Algorithm for Constrained Real-Parameter Optimization

    V.L. Huang;A.K. Qin;P.N. Suganthan

  • Unsupervised Polarimetric SAR Image Segmentation and Classification Using Region Growing With Edge Penalty

    P. Yu;A. K. Qin;D. A. Clausi

  • A review of population initialization techniques for evolutionary algorithms

    Borhan Kazimipour;Xiaodong Li;A. K. Qin

  • Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles

    Ranjie Duan;Xingjun Ma;Yisen Wang;James Bailey

  • Private spatial data aggregation in the local setting

    Rui Chen;Haoran Li;A. K. Qin;Shiva Prasad Kasiviswanathan

  • Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images

    Yue Wu;Jiaheng Li;Yongzhe Yuan;A. K. Qin

  • Self-Regulated Evolutionary Multitask Optimization

    Xiaolong Zheng;A. K. Qin;Maoguo Gong;Deyun Zhou

  • Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results

    Yuan Yuan;Yew-Soon Ong;Liang Feng;A. K. Qin

  • Linear dimensionality reduction using relevance weighted LDA

    E. K. Tang;P. N. Suganthan;X. Yao;A. K. Qin

  • Robust growing neural gas algorithm with application in cluster analysis

    A. K. Qin;P. N. Suganthan

  • Multivariate Image Segmentation Using Semantic Region Growing With Adaptive Edge Penalty

    A K Qin;David A Clausi

  • An Extended Catalog of Galaxy–Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks

    C. Jacobs;T. Collett;K. Glazebrook;E. Buckley-Geer

  • Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink

    Ranjie Duan;Xiaofeng Mao;A. K. Qin;Yuefeng Chen

  • Problem Definitions for Performance Assessment of Multi-objective Optimization Algorithms

    VL Huang;AK Qin;K Deb;E Zitzler

  • Two-hidden-layer extreme learning machine for regression and classification

    B.Y. Qu;B.F. Lang;J.J. Liang;A.K. Qin

Frequent Co-Authors

Maoguo Gong
Maoguo Gong Xidian University
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
Xiaodong Li
Xiaodong Li University of Virginia
Jing Liang
Jing Liang Zhengzhou University
Ke Tang
Ke Tang Southern University of Science and Technology
D. L. Burke
D. L. Burke Stanford University
Yun Yang
Yun Yang Swinburne University of Technology
Robert A. Gruendl
Robert A. Gruendl University of Illinois at Urbana-Champaign
David A. Clausi
David A. Clausi University of Waterloo

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