World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7551
World Ranking
8372
National Ranking
3587

William V. Stoecker 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 William V. Stoecker 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: 115 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

William V. Stoecker 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 William V. Stoecker 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

William V. Stoecker is affiliated with the Missouri University of Science and Technology in the United States. Their research primarily focuses on the intersection of medicine and computer science, with a special emphasis on oncology, epidemiology, and artificial intelligence.

The scientist's work spans several subfields including radiology, nuclear medicine and imaging, and computer vision and pattern recognition. Key research topics covered in their publications include:

  • AI in cancer detection
  • Cutaneous melanoma detection and management
  • Nonmelanoma skin cancer studies
  • Cervical cancer and HPV research
  • Radiomics and machine learning in medical imaging
  • Genetic and rare skin diseases
  • Cell image analysis techniques

William V. Stoecker has contributed to a number of research papers in prominent scientific venues. Recent papers include:

  • "ChimeraNet: U-Net for Hair Detection in Dermoscopic Skin Lesion Images," 2022, published in Journal of Digital Imaging
  • "Improving Automatic Melanoma Diagnosis Using Deep Learning-Based Segmentation of Irregular Networks," 2023, published in Cancers
  • "EpithNet: Deep Regression for Epithelium Segmentation in Cervical Histology Images," 2020, published in Journal of Pathology Informatics
  • "DeepCIN: Attention-Based Cervical histology Image Classification with Sequential Feature Modeling for Pathologist-Level Accuracy," 2020, published in Journal of Pathology Informatics
  • "Automated Cervical Digitized Histology Whole-Slide Image Analysis Toolbox," 2021, published in Journal of Pathology Informatics

The scientist frequently publishes in venues such as Zenodo (CERN European Organization for Nuclear Research), Journal of Pathology Informatics, Journal of Imaging Informatics in Medicine, Journal of Digital Imaging, and Skin Research and Technology.

Frequent co-authors collaborating with William V. Stoecker include Jason Hagerty, Norsang Lama, Anand K. Nambisan, R. Joe Stanley, and Akanksha Maurya. These collaborations have contributed to multiple papers across the scientist's fields of interest, reflecting continued research partnerships.

Best Publications

  • A Methodological Approach to the Classification of Dermoscopy Images

    M. Emre Celebi;Hassan A. Kingravi;Bakhtiyar Uddin;Hitoshi Iyatomi

  • Lesion border detection in dermoscopy images.

    M.Emre Celebi;Hitoshi Iyatomi;Gerald Schaefer;William V. Stoecker

  • Neural network diagnosis of malignant melanoma from color images

    F. Ercal;A. Chawla;W.V. Stoecker;Hsi-Chieh Lee

  • Border detection in dermoscopy images using statistical region merging.

    M. Emre Celebi;Hassan A. Kingravi;Hitoshi Iyatomi;Y. Alp Aslandogan

  • Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes.

    Bulent Erkol;Randy Hays Moss;R. Joe Stanley;William V. Stoecker

  • Unsupervised color image segmentation: with application to skin tumor borders

    G.A. Hance;S.E. Umbaugh;R.H. Moss;W.V. Stoecker

  • Accuracy in melanoma detection: A 10-year multicenter survey

    Giuseppe Argenziano;Lorenzo Cerroni;Iris Zalaudek;Stefania Staibano

  • Unsupervised border detection in dermoscopy images

    M. Emre Celebi;Y. Alp Aslandogan;William V. Stoecker;Hitoshi Iyatomi

  • Automatic detection of blue-white veil and related structures in dermoscopy images

    M. Emre Celebi;Hitoshi Iyatomi;William V. Stoecker;Randy H. Moss

  • Deep Learning and Handcrafted Method Fusion: Higher Diagnostic Accuracy for Melanoma Dermoscopy Images

    Jason R. Hagerty;R. Joe Stanley;Haidar A. Almubarak;Norsang Lama

  • Independent Histogram Pursuit for Segmentation of Skin Lesions

    D.D. Gomez;C. Butakoff;B.K. Ersboll;W. Stoecker

  • Automatic color segmentation algorithms-with application to skin tumor feature identification

    S.E. Umbaugh;R.H. Moss;W.V. Stoecker;G.A. Hance

  • Automatic color segmentation of images with application to detection of variegated coloring in skin tumors

    S.E. Umbaugh;R.H. Moss;W.V. Stoecker

  • Automatic detection of asymmetry in skin tumors.

    William V. Stoecker;William Weiling Li;Randy Hays Moss

  • A relative color approach to color discrimination for malignant melanoma detection in dermoscopy images.

    R. Joe Stanley;William V. Stoecker;Randy Hays Moss

  • Skin lesion classification using relative color features

    Yue (Iris) Cheng;Ragavendar Swamisai;Scott E. Umbaugh;Randy H. Moss

  • Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels.

    Sudhir Sornapudi;Ronald Joe Stanley;William V Stoecker;Haidar Almubarak

  • Differentiation among basal cell carcinoma, benign lesions, and normal skin using electric impedance

    D.G. Beetner;S. Kapoor;S. Manjunath;Xiangyang Zhou

  • Detection of granularity in dermoscopy images of malignant melanoma using color and texture features.

    William V. Stoecker;Mark Wronkiewiecz;Raeed H. Chowdhury;R. Joe Stanley

  • A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images.

    R.Joe Stanley;Randy Hays Moss;William Van Stoecker;Chetna Aggarwal

  • Detection of asymmetric blotches (asymmetric structureless areas) in dermoscopy images of malignant melanoma using relative color.

    William V. Stoecker;Kapil Gupta;R. Joe Stanley;Randy Hays Moss

Frequent Co-Authors

Randy Hays Moss
Randy Hays Moss Missouri University of Science and Technology
M. Emre Celebi
M. Emre Celebi University of Central Arkansas
Sameer Antani
Sameer Antani National Institutes of Health
Ashfaq A. Marghoob
Ashfaq A. Marghoob Memorial Sloan Kettering Cancer Center
Giuseppe Argenziano
Giuseppe Argenziano University of Campania "Luigi Vanvitelli"
George R. Thoma
George R. Thoma National Institutes of Health
H. Peter Soyer
H. Peter Soyer University of Queensland
Gerald Schaefer
Gerald Schaefer Loughborough University
Allan C. Halpern
Allan C. Halpern Memorial Sloan Kettering Cancer Center
Iris Zalaudek
Iris Zalaudek University of Trieste

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring associates degrees online can be a great first step for students interested in computer science, offering foundational knowledge and flexible options for beginners. Many US colleges now provide these accessible programs, making it easy to get started from anywhere.

For those looking to advance quickly, the shortest online masters degree programs can provide an accelerated path to higher qualifications in technology fields—some can be completed in just a year.

If you are considering which direction to take, it’s helpful to research what masters program should i do to ensure your education leads to in-demand skills and strong career prospects in computer science or IT.

Cost is a major factor for many students. Fortunately, the cheapest online colleges now offer quality computer science degrees, making this field more accessible than ever.

Best Scientists Citing William V. Stoecker

Trending Scientists

Recently Published Articles