World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
10563
World Ranking
5333
National Ranking
158

Overview

Junbin Gao is affiliated with the University of Sydney in Australia and has a research portfolio centered on computer science with a focus on artificial intelligence and its applications. Their work spans multiple subfields including artificial intelligence, computer vision and pattern recognition, statistical and nonlinear physics, signal processing, and building and construction.

The scientist has published extensively in topics related to advanced graph neural networks, face and expression recognition, traffic prediction and management techniques, complex network analysis techniques, topic modeling, domain adaptation and few-shot learning, as well as text and document classification technologies. These research topics reflect a broad engagement with contemporary challenges in machine learning and data analysis.

Frequent collaborators have included Baocai Yin, Yongli Hu, Yanfeng Sun, Andi Han, and Boyue Wang. This network of coauthors indicates active collaboration within their research community.

The venues where Gao's work has been regularly published include:

  • arXiv (Cornell University)
  • IEEE Transactions on Neural Networks and Learning Systems
  • SSRN Electronic Journal
  • Neural Networks
  • IEEE Transactions on Knowledge and Data Engineering

Notable recent papers include:

  • Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction, 2020, IEEE Transactions on Intelligent Transportation Systems
  • Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review, 2022, IEEE Reviews in Biomedical Engineering
  • Neighborhood Linear Discriminant Analysis, 2021, Pattern Recognition
  • Hierarchical Graph Convolution Network for Traffic Forecasting, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Dynamic Graph Convolution Network for Traffic Forecasting Based on Latent Network of Laplace Matrix Estimation, 2020, IEEE Transactions on Intelligent Transportation Systems

The volume and scope of Gao's research reflect a significant concentration on graph neural networks and their application to real-world problems such as traffic forecasting and medical image analysis. The publication venues indicate a focus on high-impact journals and conferences within computer science and engineering disciplines.

Best Publications

  • Laplacian Regularized Low-Rank Representation and Its Applications

    Ming Yin;Junbin Gao;Zhouchen Lin

  • Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization

    Yang Wang;Lin Wu;Xuemin Lin;Junbin Gao

  • Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

    Unknown

  • Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction

    Kan Guo;Yongli Hu;Zhen Qian;Hao Liu

  • A review on applications of wavelet transform techniques in chemical analysis: 1989–1997

    Alexander Kai-man Leung;Foo-tim Chau;Jun-bin Gao

  • Some Remarks on Kalman Filters for the Multisensor Fusion

    Junbin Gao;Chris J. Harris

  • Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition

    Lin Wu;Yang Wang;Xue Li;Junbin Gao

  • Where-and-When to Look: Deep Siamese Attention Networks for Video-Based Person Re-Identification

    Lin Wu;Yang Wang;Junbin Gao;Xue Li

  • Chemometrics: From Basics to Wavelet Transform

    F.T. Chau;Y.Z. Liang;Junbin Gao;X.G. Shao

  • Neighborhood Linear Discriminant Analysis

    Fa Zhu;Junbin Gao;Jian Yang;Ning Ye

  • Multiview Subspace Clustering via Tensorial t-Product Representation

    Ming Yin;Junbin Gao;Shengli Xie;Yi Guo

  • A Probabilistic Framework for SVM Regression and Error Bar Estimation

    J. B. Gao;S. R. Gunn;C. J. Harris;M. Brown

  • Hierarchical Graph Convolution Network for Traffic Forecasting

    Kan Guo;Yongli Hu;Yanfeng Sun;Sean Qian

  • Deep adaptive feature embedding with local sample distributions for person re-identification

    Lin Wu;Yang Wang;Junbin Gao;Xue Li

  • Dynamic Graph Convolution Network for Traffic Forecasting Based on Latent Network of Laplace Matrix Estimation

    Kan Guo;Yongli Hu;Zhen Qian;Yanfeng Sun

  • Sparse kernel learning with LASSO and Bayesian inference algorithm.

    Junbin Gao;Paul Wing Hing Kwan;Daming Shi

  • Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering

    Ming Yin;Junbin Gao;Zhouchen Lin;Qinfeng Shi

  • What-and-where to match: Deep spatially multiplicative integration networks for person re-identification

    Lin Wu;Yang Wang;Xue Li;Xue Li;Junbin Gao

  • Deep Learning Models for Retinal Blood Vessels Segmentation: A Review

    Toufique Ahmed Soomro;Ahmed J. Afifi;Lihong Zheng;Shafiullah Soomro

  • Subspace Clustering for Sequential Data

    Stephen Tierney;Junbin Gao;Yi Guo

  • Simulated maximum likelihood method for estimating kinetic rates in gene expression

    Tianhai Tian;Songlin Xu;Junbin Gao;Kevin Burrage

Frequent Co-Authors

Manoranjan Paul
Manoranjan Paul Charles Sturt University
Sheng Chen
Sheng Chen University of Southampton
Baocai Yin
Baocai Yin Beijing University of Technology
Zhouchen Lin
Zhouchen Lin Peking University
Shengli Xie
Shengli Xie Guangdong University of Technology
Steve R. Gunn
Steve R. Gunn University of Southampton
Xue Li
Xue Li University of Queensland
Shuicheng Yan
Shuicheng Yan National University of Singapore
Qinfeng Shi
Qinfeng Shi University of Adelaide
Dacheng Tao
Dacheng Tao Nanyang Technological University

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