World's Best Scientists 2026 revealed!
Hamid R. Tizhoosh

Hamid R. Tizhoosh

D-Index & Metrics

Computer Science

D-Index
52
Citations
14083
World Ranking
5005
National Ranking
2327

Hamid R. Tizhoosh 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 Hamid R. Tizhoosh 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: 280 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Hamid R. Tizhoosh 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 Hamid R. Tizhoosh 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: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Hamid R. Tizhoosh is a researcher affiliated with the Mayo Clinic in the United States. Their work broadly spans the fields of Computer Science and Medicine, with a particular focus on applications of Artificial Intelligence in medical imaging and diagnostics.

The main fields of study for Tizhoosh include:

  • Computer Science
  • Medicine

Within these fields, their research often concentrates on the following subfields:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Oncology
  • Molecular Biology

Key research topics covered throughout their publications include:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Digital Imaging for Blood Diseases
  • Image Retrieval and Classification Techniques
  • Colorectal Cancer Screening and Detection
  • COVID-19 diagnosis using AI
  • Cell Image Analysis Techniques

Tizhoosh has contributed to numerous scientific articles published across multiple journals and venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Scientific Reports
  • Research Square (Research Square)
  • Lecture Notes in Computer Science
  • American Journal Of Pathology

Several recently published papers highlight the scope of their research work, including:

  • Federated learning and differential privacy for medical image analysis, 2022, Scientific Reports
  • Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides, 2021, Medical Image Analysis
  • Yottixel - An Image Search Engine for Large Archives of Histopathology Whole Slide Images, 2020, Medical Image Analysis
  • Decentralized federated learning through proxy model sharing, 2023, Nature Communications
  • Automated bone marrow cytology using deep learning to generate a histogram of cell types, 2022, Communications Medicine

Throughout their career, Tizhoosh has frequently collaborated with a group of co-authors, including:

  • Morteza Babaie
  • Shivam Kalra
  • Clinton J.V. Campbell
  • Taher Dehkharghanian
  • Shahryar Rahnamayan

Best Publications

  • Opposition-Based Learning: A New Scheme for Machine Intelligence

    H.R. Tizhoosh

  • Opposition-Based Differential Evolution

    S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

  • Artificial intelligence and digital pathology: Challenges and opportunities

    Hamid Reza Tizhoosh;Liron Pantanowitz

  • Quasi-oppositional Differential Evolution

    S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

  • A novel population initialization method for accelerating evolutionary algorithms

    Shahryar Rahnamayan;Hamid R. Tizhoosh;Magdy M. A. Salama

  • Opposition versus randomness in soft computing techniques

    Shahryar Rahnamayan;Hamid R. Tizhoosh;Magdy M. A. Salama

  • Image thresholding using type II fuzzy sets

    Hamid R. Tizhoosh

  • Federated learning and differential privacy for medical image analysis

    Unknown

  • Opposition-Based Reinforcement Learning

    Hamid R. Tizhoosh

  • Opposition-Based Differential Evolution Algorithms

    S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

  • Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides.

    Abtin Riasatian;Morteza Babaie;Danial Maleki;Shivam Kalra

  • Convolutional neural networks for histopathology image classification: Training vs. Using pre-trained networks

    Brady Kieffer;Morteza Babaie;Shivam Kalra;H. R. Tizhoosh

  • Opposition-Based Differential Evolution for Optimization of Noisy Problems

    S. Rahnamayan;H.R. Tizhoosh;M.M.A. Salama

  • Improving the Convergence of Backpropagation by Opposite Transfer Functions

    M. Ventresca;H.R. Tizhoosh

  • Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images

    H. Bustince;M. Pagola;E. Barrenechea;J. Fernandez

  • Decentralized federated learning through proxy model sharing

    Unknown

  • Fuzzy image processing

    Horst Haußecker;Hamid R. Tizhoosh

  • Yottixel - An Image Search Engine for Large Archives of Histopathology Whole Slide Images.

    Shivam Kalra;Hamid R. Tizhoosh;Charles Choi;Sultaan Shah

  • Fast fuzzy edge detection

    H.R. Tizhoosh

  • IRIS Segmentation: Detecting Pupil, Limbus and Eyelids

    E.M. Arvacheh;H.R. Tizhoosh

  • Filter fusion for image enhancement using reinforcement learning

    F. Sahba;H.R. Tizhoosh

  • A sequential search-space shrinking using CNN transfer learning and a Radon projection pool for medical image retrieval

    Amin Khatami;Morteza Babaie;Morteza Babaie;HR Tizhoosh;Abbas Khosravi

  • Medical Image Classification via SVM Using LBP Features from Saliency-Based Folded Data

    Zehra Camlica;H.R. Tizhoosh;Farzad Khalvati

Frequent Co-Authors

Shahryar Rahnamayan
Shahryar Rahnamayan University of Ontario Institute of Technology
Magdy M. A. Salama
Magdy M. A. Salama University of Waterloo
Fakhri Karray
Fakhri Karray Mohamed bin Zayed University of Artificial Intelligence
Mohamed S. Kamel
Mohamed S. Kamel University of Waterloo
Saeid Nahavandi
Saeid Nahavandi Swinburne University of Technology
Abbas Khosravi
Abbas Khosravi Deakin University
Ali Ghodsi
Ali Ghodsi University of Waterloo
Andrew K. C. Wong
Andrew K. C. Wong University of Waterloo
Aaron Fenster
Aaron Fenster University of Western Ontario
Graham W. Taylor
Graham W. Taylor University of Guelph

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