World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
10763
World Ranking
10987
National Ranking
146

Overview

Kezhi Mao is affiliated with Nanyang Technological University in Singapore and has contributed extensively to the field of Computer Science, with a focus on Artificial Intelligence and related subfields. Their research encompasses areas such as Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Mechanical Engineering, and Infectious Diseases.

The scientist has published over a hundred works, with notable activity in Artificial Intelligence and Computer Vision specifically. Their main research topics include Human Pose and Action Recognition, Topic Modeling, Domain Adaptation and Few-Shot Learning, Natural Language Processing Techniques, Video Surveillance and Tracking Methods, Advanced Text Analysis Techniques, and Anomaly Detection Techniques and Applications.

Frequent collaborators of Kezhi Mao include the following researchers:

  • Yuecong Xu
  • Jianfei Yang
  • Haozhi Cao
  • Jianxiong Yin
  • Simon See

The scientist has published in various venues, with multiple contributions to:

  • arXiv (Cornell University)
  • Neurocomputing
  • Expert Systems with Applications
  • IEEE Journal of Emerging and Selected Topics in Power Electronics
  • SSRN Electronic Journal

Selected recent papers authored by or coauthored with Kezhi Mao include:

  • "Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress" (2021), IEEE Journal of Emerging and Selected Topics in Power Electronics
  • "Particle swarm optimization with state-based adaptive velocity limit strategy" (2021), Neurocomputing
  • "Improving convolutional neural network for text classification by recursive data pruning" (2020), Neurocomputing
  • "Aligning Correlation Information for Domain Adaptation in Action Recognition" (2022), IEEE Transactions on Neural Networks and Learning Systems
  • "Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency" (2023), IEEE Journal of Emerging and Selected Topics in Power Electronics

Best Publications

  • Deep learning and its applications to machine health monitoring

    Rui Zhao;Ruqiang Yan;Zhenghua Chen;Kezhi Mao

  • Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks

    Rui Zhao;Dongzhe Wang;Ruqiang Yan;Kezhi Mao

  • Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks.

    Rui Zhao;Ruqiang Yan;Jinjiang Wang;Kezhi Mao

  • Representational learning with ELMs for big data

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

  • Extreme Learning Machine

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

  • Probabilistic neural-network structure determination for pattern classification

    K.Z. Mao;K.-C. Tan;W. Ser

  • Can threshold networks be trained directly

    Guang-Bin Huang;Qin-Yu Zhu;K.Z. Mao;Chee-Kheong Siew

  • Orthogonal forward selection and backward elimination algorithms for feature subset selection

    K.Z. Mao

  • Automatic detection of cyberbullying on social networks based on bullying features

    Rui Zhao;Anna Zhou;Kezhi Mao

  • Fuzzy Bag-of-Words Model for Document Representation

    Rui Zhao;Kezhi Mao

  • Machine health monitoring with LSTM networks

    Rui Zhao;Jinjiang Wang;Ruqiang Yan;Kezhi Mao

  • Supervised learning-based cell image segmentation for P53 immunohistochemistry

    K.Z. Mao;Peng Zhao;Puay-Hoon Tan

  • Feature subset selection for support vector machines through discriminative function pruning analysis

    K.Z. Mao

  • RBF neural network center selection based on Fisher ratio class separability measure

    K.Z. Mao

  • Robust Feature Selection for Microarray Data Based on Multicriterion Fusion

    Feng Yang;K. Z. Mao

  • Knowledge-oriented convolutional neural network for causal relation extraction from natural language texts

    Pengfei Li;Kezhi Mao

  • Deep Learning and Its Applications to Machine Health Monitoring: A Survey

    Rui Zhao;Ruqiang Yan;Zhenghua Chen;Kezhi Mao

  • Cyberbullying Detection Based on Semantic-Enhanced Marginalized Denoising Auto-Encoder

    Rui Zhao;Kezhi Mao

  • Algorithms for minimal model structure detection in nonlinear dynamic system identification

    K. Z. Mao;S. A. Billings

  • Neuron selection for RBF neural network classifier based on data structure preserving criterion

    K.Z. Mao;Guang-Bin Huang

  • Identifying critical variables of principal components for unsupervised feature selection

    K.Z. Mao

Frequent Co-Authors

Jianfei Yang
Jianfei Yang Nanyang Technological University
Ruqiang Yan
Ruqiang Yan Xi'an Jiaotong University
Guang-Bin Huang
Guang-Bin Huang Nanyang Technological University
Amaury Lendasse
Amaury Lendasse University of Houston
Tianyou Chai
Tianyou Chai Northeastern University
Hong Zhang
Hong Zhang University of Alberta
Kar-Ann Toh
Kar-Ann Toh Yonsei University
Peng Wang
Peng Wang Nanyang Technological University
Robert X. Gao
Robert X. Gao Case Western Reserve University
Changyun Wen
Changyun Wen Nanyang Technological University

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