World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
7595
World Ranking
13851
National Ranking
538

Alexander Wong publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Alexander Wong sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 269 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Alexander Wong D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Alexander Wong sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Alexander Wong is a researcher primarily affiliated with the University of Waterloo in Canada. Their work spans mainly the fields of Medicine and Computer Science, with a strong focus on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Health Informatics, and Pulmonary and Respiratory Medicine.

The scientist's research covers various specialized topics including COVID-19 diagnosis using AI, Radiomics and Machine Learning in Medical Imaging, Advanced Neural Network Applications, Artificial Intelligence in Healthcare and Education, AI in cancer detection, Advanced Neuroimaging Techniques and Applications, and MRI in cancer diagnosis.

Notable recent papers authored or co-authored by Alexander Wong include:

  • "COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images," 2020, Scientific Reports
  • "COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest CT Images," 2020, Frontiers in Medicine
  • "COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images," 2020, arXiv (Cornell University)
  • "COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 From Chest CT Images Through Bigger, More Diverse Learning," 2022, Frontiers in Medicine
  • "Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays," 2021, Scientific Reports

Alexander Wong has frequently collaborated with a range of co-authors, including Hayden Gunraj, Pengcheng Xi, Ashkan Ebadi, Mohammad Javad Shafiee, and Chi-en Amy Tai.

The scientist's publications have appeared predominantly in venues such as arXiv (Cornell University), Sensors, Scientific Reports, Research Square, and the Journal of Computational Vision and Imaging Systems. This distribution indicates an emphasis on venues that accommodate interdisciplinary research spanning both the computational and medical domains.

Best Publications

  • Massively parallel digital transcriptional profiling of single cells

    Grace X. Y. Zheng;Jessica M. Terry;Phillip Belgrader;Paul Ryvkin

  • COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.

    Linda Wang;Zhong Qiu Lin;Alexander Wong

  • The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    Leming Shi;Laura H. Reid;Wendell D. Jones;Richard Shippy

  • Haplotyping germline and cancer genomes with high-throughput linked-read sequencing

    Grace X Y Zheng;Billy T Lau;Michael Schnall-Levin;Mirna Jarosz

  • Measuring Diversity: Experimental Design of Combinatorial Libraries for Drug Discovery

    Eric J. Martin;Jeffrey M. Blaney;Michael A. Siani;David C. Spellmeyer

  • Lung Nodule Classification Using Deep Features in CT Images

    Devinder Kumar;Alexander Wong;David A. Clausi

  • Potential multiparticle entanglement measure

    Alexander Wong;Nelson Christensen

  • Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

    Mohammad Javad Shaifee;Brendan Chywl;Francis Li;Alexander Wong

  • Squeeze-and-Attention Networks for Semantic Segmentation

    Zilong Zhong;Zhong Qiu Lin;Rene Bidart;Xiaodan Hu

  • COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest CT Images

    Hayden Gunraj;Linda Wang;Alexander Wong

  • ARRSI: Automatic Registration of Remote-Sensing Images

    A. Wong;D.A. Clausi

  • A nonlocal-means approach to exemplar-based inpainting

    A. Wong;J. Orchard

  • Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer.

    Yucheng Zhang;Anastasia Oikonomou;Alexander Wong;Masoom A. Haider

  • Intra-retinal layer segmentation in optical coherence tomography images

    Akshaya Mishra;Alexander Wong;Kostadinka Bizheva;David A. Clausi

  • COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images

    Linda Wang;Alexander Wong

  • Fast and Accurate k-means For Large Datasets

    Michael Shindler;Alex Wong;Adam W. Meyerson

  • General Bayesian estimation for speckle noise reduction in optical coherence tomography retinal imagery

    Alexander Wong;Akshaya Mishra;Kostadinka Bizheva;David A Clausi

  • Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

    Farzad Khalvati;Farzad Khalvati;Alexander Wong;Masoom A. Haider;Masoom A. Haider

  • MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection

    Andrew Cameron;Farzad Khalvati;Masoom A. Haider;Alexander Wong

  • Statistical Textural Distinctiveness for Salient Region Detection in Natural Images

    Christian Scharfenberger;Alexander Wong;Khalil Fergani;John S. Zelek

  • High-Level Intuitive Features (HLIFs) for Intuitive Skin Lesion Description

    Robert Amelard;Jeffrey Glaister;Alexander Wong;David A. Clausi

  • COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse Learning.

    Hayden Gunraj;Ali Sabri;David Koff;Alexander Wong

  • Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

    Mohammad Javad Shafiee;Brendan Chywl;Francis Li;Alexander Wong

  • Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction

    Devinder Kumar;Audrey G. Chung;Mohammad J. Shaifee;Farzad Khalvati;Farzad Khalvati

  • Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation

    William J. McNally;Kanav Vats;Alexander Wong;John McPhee

  • Extended Knowledge-Based Reasoning Approach to Spectrum Sensing for Cognitive Radio

    Xiao Yu Wang;A. Wong;Pin-Han Ho

  • Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection

    Alexander Wong;Mohammad Javad Shafiee;Francis Li;Brendan Chwyl

  • MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection

    Farzad Khalvati;Junjie Zhang;Audrey G. Chung;Mohammad Javad Shafiee

  • COVIDx-US -- An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analytics

    Ashkan Ebadi;Pengcheng Xi;Alexander MacLean;Stéphane Tremblay

  • Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living.

    T. Beltrame;R. Amelard;A. Wong;R. L. Hughson

  • Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays

    A. Wong;Z. Q. Lin;L. Wang;A. G. Chung

  • Structure-Guided Statistical Textural Distinctiveness for Salient Region Detection in Natural Images

    Christian Scharfenberger;Alexander Wong;David A. Clausi

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