World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6356
World Ranking
12019
National Ranking
756

Tuan D. Pham 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 Tuan D. Pham 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: 368 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Tuan D. Pham 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 Tuan D. Pham 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Tuan D. Pham is affiliated with Queen Mary University of London in the United Kingdom. Their research intersects the fields of Medicine and Computer Science, with a total of 107 and 83 publications respectively. The scientist's subfields of study include Radiology, Nuclear Medicine and Imaging; Artificial Intelligence; Signal Processing; Computer Vision and Pattern Recognition; and Cognitive Neuroscience.

The primary topics covered in their work encompass Radiomics and Machine Learning in Medical Imaging, AI in cancer detection, Advanced Malware Detection Techniques, Anomaly Detection Techniques and Applications, COVID-19 diagnosis using AI, Network Security and Intrusion Detection, and Artificial Intelligence in Healthcare and Education.

Recent significant papers authored by Tuan D. Pham include:

  • Classification of COVID-19 chest X-rays with deep learning: new models or fine tuning?, 2020, Health Information Science and Systems
  • A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks, 2020, Scientific Reports

Frequent co-authors include:

  • Vinayakumar Ravi
  • Simon Holmes
  • Paul Coulthard
  • Chuanwen Fan
  • Xiao-Feng Sun

Tuan D. Pham has published primarily in venues such as bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Scientific Reports, Ministry of Science and Technology Vietnam, and Europhysics Letters (EPL).

They have contributed to the book titled Advances in Artificial Intelligence, Computation, and Data Science, published by Springer Nature (Netherlands) in 2021.

Best Publications

  • Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition

    Zheru Chi;Hong Yan;Tuan Pham

  • DUNet: A deformable network for retinal vessel segmentation

    Qiangguo Jin;Zhaopeng Meng;Zhaopeng Meng;Tuan D. Pham;Qi Chen

  • Crowdsourcing the creation of image segmentation algorithms for connectomics

    Ignacio Arganda-Carreras;Srinivas C. Turaga;Daniel R. Berger;Dan Cireşan

  • Classification of COVID-19 chest X-rays with deep learning: new models or fine tuning?

    Tuan D. Pham

  • A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks

    Tuan D. Pham

  • Deep learning-based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images.

    Vinayakumar Ravi;Harini Narasimhan;Chinmay Chakraborty;Tuan D. Pham

  • A probabilistic measure for alignment-free sequence comparison

    Tuan D. Pham;Johannes Zuegg

  • Fuzzy finite element analysis of a foundation on an elastic soil medium

    S. Valliappan;T. D. Pham

  • How to Collect Segmentations for Biomedical Images? A Benchmark Evaluating the Performance of Experts, Crowdsourced Non-experts, and Algorithms

    Danna Gurari;Diane Theriault;Mehrnoosh Sameki;Brett Isenberg

  • Time-frequency time-space LSTM for robust classification of physiological signals

    Tuan D. Pham

  • Unconstrained logo detection in document images

    Tuan D. Pham

  • Attention deep learning‐based large‐scale learning classifier for Cassava leaf disease classification

    Vinayakumar Ravi;Vasundhara Acharya;Tuan D. Pham

  • Human Face Image Recognition

    Ali Reza Mirhosseini;Hong Yan;Kin-Man Lam;Tuan Pham

  • Elasto‐plastic finite element analysis with fuzzy parameters

    S. Valliappan;T. D. Pham

  • Gait Classificaiton in Children with Cerebral Palsy by Bayesian Approach

    Bai-ling Zhang;Yanchun Zhang;T.D. Pham;R.K. Begg

  • Image segmentation using probabilistic fuzzy c-means clustering

    T.D. Pham

  • Fuzzy recurrence plots

    Tuan D. Pham

  • Color image segmentation using fuzzy integral and mountain clustering

    Tuan D. Pham;Hong Yan

  • Integrative analysis of next generation sequencing for small non-coding RNAs and transcriptional regulation in Myelodysplastic Syndromes

    Dominik Beck;Dominik Beck;Steve Ayers;Jianguo Wen;Miriam B. Brandl;Miriam B. Brandl

  • Region Based Parallel Hierarchy Convolutional Neural Network for Automatic Facial Nerve Paralysis Evaluation

    Xin Liu;Yifan Xia;Hui Yu;Junyu Dong

  • Time-Independent Prediction of Burn Depth Using Deep Convolutional Neural Networks.

    Marco Domenico Cirillo;Robin Mirdell;Folke Sjöberg;Tuan D Pham

  • Texture Analysis and Synthesis of Malignant and Benign Mediastinal Lymph Nodes in Patients with Lung Cancer on Computed Tomography.

    Tuan D Pham;Yuzuru Watanabe;Mitsunori Higuchi;Hiroyuki Suzuki

  • Analysis of Microarray Gene Expression Data

    Tuan D. Pham;Christine Wells;Denis I. Crane

Frequent Co-Authors

Xiaobo Zhou
Xiaobo Zhou The University of Texas Health Science Center at Houston
Changming Sun
Changming Sun Commonwealth Scientific and Industrial Research Organisation
Hong Yan
Hong Yan City University of Hong Kong
Michael Wagner
Michael Wagner University of Canberra
Stephen T. C. Wong
Stephen T. C. Wong Houston Methodist
James A. Hamilton
James A. Hamilton Boston University
Xiaoyi Jiang
Xiaoyi Jiang University of Münster
Xiuping Jia
Xiuping Jia University of New South Wales
Junyu Dong
Junyu Dong Ocean University of China
Robert T. Furbank
Robert T. Furbank Australian National University

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