World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
14584
World Ranking
4248
National Ranking
66

Overview

Lipo Wang is affiliated with Nanyang Technological University in Singapore and focuses research efforts primarily in the fields of Computer Science and Engineering. Their work encompasses various subfields, including Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Biomedical Engineering, and Electrical and Electronic Engineering.

The scientist's research covers multiple topics, notably Medical Image Segmentation Techniques, EEG and Brain-Computer Interfaces, Anomaly Detection Techniques and Applications, Human Pose and Action Recognition, Stock Market Forecasting Methods, Face Recognition and Analysis, and Generative Adversarial Networks and Image Synthesis.

Selected recent papers authored or coauthored by Lipo Wang include:

  • "3D Deep Learning on Medical Images: A Review," 2020, MDPI (MDPI AG)
  • "Shallow 3D CNN for Detecting Acute Brain Hemorrhage From Medical Imaging Sensors," 2020, IEEE Sensors Journal
  • "Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting," 2020, Information Sciences
  • "Sample-Based Data Augmentation Based on Electroencephalogram Intrinsic Characteristics," 2022, IEEE Journal of Biomedical and Health Informatics
  • "TFormer: A time-frequency Transformer with batch normalization for driver fatigue recognition," 2024, Advanced Engineering Informatics

Frequent collaborators include:

  • Yaoli Wang
  • Olga Sourina
  • Ruilin Li
  • Pratik Chattopadhyay
  • Basim Azam

Lipo Wang has published extensively in venues such as arXiv (Cornell University), SSRN Electronic Journal, IEEE Sensors Journal, Methods, and Journal of Artificial Intelligence and Soft Computing Research.

The scientist's book publications span several publishers, including:

  • Springer International Publishing, with works such as "Communication and Intelligent Systems" (2022, 2023) and "Machine Intelligence for Research and Innovations" (2024)
  • Springer Science+Business Media, publishing "Communications, Networking, and Information Systems" and "Big Data and Cloud Computing" in 2023
  • Springer Nature, with "Proceedings of Academia-Industry Consortium for Data Science" (2022)
  • World Scientific, with "EEG Signal Classification Using Machine Learning" set for 2025

The scope of Lipo Wang's work reflects a combination of theoretical and applied research across multiple interconnected areas within computer science and engineering disciplines.

Best Publications

  • Support Vector Machines: Theory and Applications

    Lipo Wang

  • Deep Learning Applications in Medical Image Analysis

    Justin Ker;Lipo Wang;Jai Rao;Tchoyoson Lim

  • Data mining with computational intelligence

    Lipo Wang

  • 3D Deep Learning on Medical Images: A Review.

    Satya Prakash Singh;Lipo Wang;Sukrit Gupta;Haveesh Goli

  • Advances in Natural Computation

    Lipo Wang;Ke Chen;Yew Soon Ong

  • Accurate Cancer Classification Using Expressions of Very Few Genes

    Lipo Wang;Feng Chu;Wei Xie

  • Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance

    Xiuju Fu;Lipo Wang

  • Feature selection methods for big data bioinformatics: A survey from the search perspective.

    Lipo Wang;Yaoli Wang;Qing Chang

  • Domain Adaptation Techniques for EEG-Based Emotion Recognition: A Comparative Study on Two Public Datasets

    Zirui Lan;Olga Sourina;Lipo Wang;Reinhold Scherer

  • On chaotic simulated annealing

    L. Wang;K. Smith

  • Real-time EEG-based emotion monitoring using stable features

    Zirui Lan;Olga Sourina;Lipo Wang;Yisi Liu

  • Saliency-Based Defect Detection in Industrial Images by Using Phase Spectrum

    Xiaolong Bai;Yuming Fang;Weisi Lin;Lipo Wang

  • Applications of support vector machines to cancer classification with microarray data.

    Feng Chu;Lipo Wang

  • A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing

    Lipo Wang;Sa Li;F. Tian;Xiuju Fu

  • An efficient semi-unsupervised gene selection method via spectral biclustering

    Bing Liu;C. Wan;Lipo Wang

  • EEG Based Stress Monitoring

    Xiyuan Hou;Yisi Liu;Olga Sourina;Yun Rui Eileen Tan

  • Image Thresholding Improves 3-Dimensional Convolutional Neural Network Diagnosis of Different Acute Brain Hemorrhages on Computed Tomography Scans

    Justin Ker;Satya Prakash Singh;Yeqi Bai;Jai Rao

  • STEW: Simultaneous Task EEG Workload Data Set

    W. L. Lim;O. Sourina;L. P. Wang

  • OSCILLATIONS AND CHAOS IN NEURAL NETWORKS : AN EXACTLY SOLVABLE MODEL

    Lipo Wang;Elgar E. Pichler;John Ross

  • Automated brain histology classification using machine learning.

    Justin Ker;Yeqi Bai;Hwei Yee Lee;Jai Rao

  • A General Wrapper Approach to Selection of Class-Dependent Features

    Lipo Wang;Nina Zhou;Feng Chu

Frequent Co-Authors

Weisi Lin
Weisi Lin Nanyang Technological University
Hongkai Zhao
Hongkai Zhao Duke University
Reinhold Scherer
Reinhold Scherer University of Essex
Gernot R. Müller-Putz
Gernot R. Müller-Putz Graz University of Technology
Daniel L. Alkon
Daniel L. Alkon West Virginia University
Yew-Soon Ong
Yew-Soon Ong Nanyang Technological University
Krzysztof Cpałka
Krzysztof Cpałka Częstochowa University of Technology
Balázs Gulyás
Balázs Gulyás Nanyang Technological University
Leonard Mandel
Leonard Mandel University of Rochester
Jacek M. Zurada
Jacek M. Zurada University of Louisville

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