World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
18724
World Ranking
1611
National Ranking
216

Overview

Bin Hu is affiliated with Lanzhou University in China and specializes in research at the intersection of computer science and neuroscience. Their work encompasses a wide range of topics primarily centered on brain connectivity, brain-computer interfaces, and emotion recognition through neural data analysis.

The main fields of study for Bin Hu include:

  • Computer Science
  • Neuroscience

Their subfields of study highlight focused research areas such as:

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Experimental and Cognitive Psychology
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging

Key research topics covered in Bin Hu's publications are:

  • Functional Brain Connectivity Studies
  • EEG and Brain-Computer Interfaces
  • Emotion and Mood Recognition
  • Neural dynamics and brain function
  • Mental Health Research Topics
  • Advanced Neuroimaging Techniques and Applications
  • Heart Rate Variability and Autonomic Control

Bin Hu has published extensively with frequent appearances in several key scientific venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Computational Social Systems
  • IEEE Journal of Biomedical and Health Informatics
  • IEEE Transactions on Affective Computing
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering

The scientist collaborates regularly with several co-authors, including:

  • Xiping Hu
  • Zhijun Yao
  • Kun Qian
  • Xiaowei Li
  • Björn W. Schuller

Notable recent publications by Bin Hu cover a variety of topics related to EEG-based emotion recognition and intelligent computing systems. Examples include:

  • "EEG emotion recognition using fusion model of graph convolutional neural networks and LSTM," 2020, Applied Soft Computing
  • "EEG Based Emotion Recognition: A Tutorial and Review," 2022, ACM Computing Surveys
  • "Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach," 2020, IEEE Journal on Selected Areas in Communications
  • "Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution," 2020, IEEE Transactions on Intelligent Transportation Systems
  • "Feature-level fusion approaches based on multimodal EEG data for depression recognition," 2020, Information Fusion

Best Publications

  • Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting

    Chao Ren;Ning An;Jianzhou Wang;Lian Li

  • Energy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks

    Jiao Zhang;Xiping Hu;Zhaolong Ning;Edith C.-H. Ngai

  • Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring

    Min Chen;Yujun Ma;Jeungeun Song;Chin-Feng Lai

  • EEG emotion recognition using fusion model of graph convolutional neural networks and LSTM

    Yongqiang Yin;Xiangwei Zheng;Bin Hu;Yuang Zhang

  • Differences in Critical Success Factors in ERP Systems Implementation in Australia and China: A Cultural Analysis

    Graeme G. Shanks;Anne N. Parr;Bin Hu;Brian J. Corbitt

  • Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach

    Zhaolong Ning;Peiran Dong;Xiaojie Wang;Xiping Hu

  • Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution

    Zhaolong Ning;Kaiyuan Zhang;Xiaojie Wang;Lei Guo

  • Exploring EEG Features in Cross-Subject Emotion Recognition

    Xiang Li;Dawei Song;Peng Zhang;Yazhou Zhang

  • Feature-level fusion approaches based on multimodal EEG data for depression recognition

    Hanshu Cai;Zhidiao Qu;Zhe Li;Yi Zhang

  • A Cooperative Quality-Aware Service Access System for Social Internet of Vehicles

    Zhaolong Ning;Xiping Hu;Zhikui Chen;MengChu Zhou

  • A Joint Intrinsic-Extrinsic Prior Model for Retinex

    Bolun Cai;Xianming Xu;Kailing Guo;Kui Jia

  • Modifying the DPClus algorithm for identifying protein complexes based on new topological structures.

    Min Li;Jian-er Chen;Jian-er Chen;Jian-xin Wang;Bin Hu

  • Emotion recognition from multi-channel EEG data through Convolutional Recurrent Neural Network

    Xiang Li;Dawei Song;Peng Zhang;Guangliang Yu

  • A Pervasive Approach to EEG-Based Depression Detection

    Hanshu Cai;Jiashuo Han;Yunfei Chen;Xiaocong Sha

  • Joint Computing and Caching in 5G-Envisioned Internet of Vehicles: A Deep Reinforcement Learning-Based Traffic Control System

    Zhaolong Ning;Kaiyuan Zhang;Xiaojie Wang;Mohammad S. Obaidat

  • Job scheduling algorithm based on Berger model in cloud environment

    Baomin Xu;Chunyan Zhao;Enzhao Hu;Bin Hu

  • Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition

    Haocong Rao;Haocong Rao;Shihao Xu;Shihao Xu;Xiping Hu;Xiping Hu;Jun Cheng

  • Wearable Circular Ring Slot Antenna With EBG Structure for Wireless Body Area Network

    Guo-Ping Gao;Bin Hu;Shao-Fei Wang;Chen Yang

  • RNN Models for Dynamic Matrix Inversion: A Control-Theoretical Perspective

    Long Jin;Shuai Li;Bin Hu

  • Design of Highly Nonlinear Substitution Boxes Based on I-Ching Operators

    Tong Zhang;C. L. Philip Chen;Long Chen;Xiangmin Xu

  • Partial Computation Offloading and Adaptive Task Scheduling for 5G-enabled Vehicular Networks

    Zhaolong Ning;Peiran Dong;Xiaojie Wang;Xiping Hu

  • A Wearable PIFA With an All-Textile Metasurface for 5 GHz WBAN Applications

    Guo-Ping Gao;Chen Yang;Bin Hu;Rui-Feng Zhang

  • A Noise-Suppressing Neural Algorithm for Solving the Time-Varying System of Linear Equations: A Control-Based Approach

    Long Jin;Shuai Li;Bin Hu;Mei Liu

  • Emotion Recognition From Multimodal Physiological Signals Using a Regularized Deep Fusion of Kernel Machine

    Xiaowei Zhang;Jinyong Liu;Jian Shen;Shaojie Li

  • EEG-based mild depressive detection using feature selection methods and classifiers

    Xiaowei Li;Bin Hu;Shuting Sun;Hanshu Cai

Frequent Co-Authors

Xiping Hu
Xiping Hu Lanzhou University
Zhaolong Ning
Zhaolong Ning Chongqing University of Posts and Telecommunications
Ning Zhong
Ning Zhong Maebashi Institute of Technology
Dawei Song
Dawei Song The Open University
Long Jin
Long Jin Lanzhou University
Lei Guo
Lei Guo Beijing University of Posts and Telecommunications
Tingshao Zhu
Tingshao Zhu University of Chinese Academy of Sciences
Shuai Li
Shuai Li University of Oulu
Fei-Yue Wang
Fei-Yue Wang Chinese Academy of Sciences
MengChu Zhou
MengChu Zhou New Jersey Institute of Technology

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