2026 Guang-Bin Huang: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	77	1227	1186	24	24	236	66145

Overview

Guang-Bin Huang is affiliated with Nanyang Technological University in Singapore. Their research spans multiple fields within computer science and engineering, with a particular focus on machine learning and extreme learning machines (ELM).

The main fields of study Guang-Bin Huang contributes to include:

Computer Science
Engineering

Within these broad areas, their work addresses several subfields of study:

Artificial Intelligence
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering
Biomedical Engineering
Molecular Biology

Key topics covered by Guang-Bin Huang's research encompass:

Machine Learning and ELM
Domain Adaptation and Few-Shot Learning
Face and Expression Recognition
Neural Networks and Applications
Video Surveillance and Tracking Methods
Obstructive Sleep Apnea Research
Advanced Neural Network Applications

The following recent papers highlight their publication activity with details on publication year and venue:

Learning local discriminative representations via extreme learning machine for machine fault diagnosis (2020), published in Neurocomputing
Deep and wide feature based extreme learning machine for image classification (2020), published in Neurocomputing
Modeling Historical AIS Data For Vessel Path Prediction: A Comprehensive Treatment (2020), published in arXiv (Cornell University)
R-ELMNet: Regularized extreme learning machine network (2020), published in Neural Networks
NOx Measurements in Vehicle Exhaust Using Advanced Deep ELM Networks (2020), published in IEEE Transactions on Instrumentation and Measurement

Guang-Bin Huang frequently collaborates with a set of coauthors, including:

Yue Li
Yijie Zeng
Yuanyuan Qing
Dongshun Cui
Qi Cao

The predominant venues for their publications are:

Neurocomputing
Neural Networks
arXiv (Cornell University)
IEEE Transactions on Instrumentation and Measurement
Sleep And Breathing

In addition to journal publications, Guang-Bin Huang has contributed to book publications. Notably, they were involved in a book published by Frontiers Media titled Brain-inspired Cognition and Understanding for Next-generation AI: Computational Models, Architectures and Learning Algorithms (2023).

Best Publications

Extreme learning machine: Theory and applications

Guang-Bin Huang;Qin-Yu Zhu;Chee Kheong Siew

15076
Citations
Extreme Learning Machine for Regression and Multiclass Classification

Guang-Bin Huang;Hongming Zhou;Xiaojian Ding;Rui Zhang

6433
Citations
Extreme learning machine: a new learning scheme of feedforward neural networks

Guang-Bin Huang;Qin-Yu Zhu;Chee-Kheong Siew

5097
Citations
Universal approximation using incremental constructive feedforward networks with random hidden nodes

Guang-Bin Huang;Lei Chen;Chee-Kheong Siew

2972
Citations
A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks

Nan-Ying Liang;Guang-Bin Huang;P. Saratchandran;N. Sundararajan

2315
Citations
Extreme learning machines: a survey

Guang-Bin Huang;Dian Hui Wang;Yuan Lan

2274
Citations
Trends in extreme learning machines

Gao Huang;Guang-Bin Huang;Shiji Song;Keyou You

2166
Citations
Letters: Convex incremental extreme learning machine

Guang-Bin Huang;Lei Chen

1613
Citations
Extreme Learning Machine for Multilayer Perceptron

Jiexiong Tang;Chenwei Deng;Guang-Bin Huang

1594
Citations
An Insight into Extreme Learning Machines: Random Neurons, Random Features and Kernels

Guang-Bin Huang

1096
Citations
Rapid and brief communication: Evolutionary extreme learning machine

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

1088
Citations
Enhanced random search based incremental extreme learning machine

Guang-Bin Huang;Lei Chen

1063
Citations
Optimization method based extreme learning machine for classification

Guang-Bin Huang;Xiaojian Ding;Hongming Zhou

1062
Citations
Learning capability and storage capacity of two-hidden-layer feedforward networks

Guang-Bin Huang

969
Citations
A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation

Guang-Bin Huang;P. Saratchandran;N. Sundararajan

879
Citations
Weighted extreme learning machine for imbalance learning

Weiwei Zong;Guang-Bin Huang;Yiqiang Chen

840
Citations
Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning

Guorui Feng;Guang-Bin Huang;Qingping Lin

779
Citations
Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation functions

Guang-Bin Huang;H.A. Babri

681
Citations
Representational learning with ELMs for big data

Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou;Guang-Bin Huang;Chi Man Vong

656
Citations
Extreme Learning Machine

Erik Cambria;Guang-Bin Huang;Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou

620
Citations

Frequent Co-Authors

Zhiping Lin Nanyang Technological University

Narasimhan Sundararajan Nanyang Technological University

Yeng Chai Soh Nanyang Technological University

Wee Ser Nanyang Technological University

Erik Cambria Nanyang Technological University

Dianhui Wang La Trobe University

Zongben Xu Xi'an Jiaotong University

Amaury Lendasse University of Houston

Soujanya Poria Nanyang Technological University

Kezhi Mao Nanyang Technological University

External Links

Personal website of Guang-Bin Huang Google Scholar page

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