World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
4557
World Ranking
12697
National Ranking
240

Anna Vilanova 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 Anna Vilanova 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: 193 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Anna Vilanova 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 Anna Vilanova 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: 33 D-Index — 13th percentile

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

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

Overview

Anna Vilanova is affiliated with Eindhoven University of Technology in the Netherlands. Their research spans primarily the fields of Computer Science and Medicine, with a focus on interdisciplinary applications linking both domains.

Their subfields of study include Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Molecular Biology, and Pediatrics, Perinatology and Child Health. This diverse range highlights a concentration on computational methods applied to medical imaging and analysis.

The main research topics addressed by Anna Vilanova include:

  • Data Visualization and Analytics
  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Fetal and Pediatric Neurological Disorders
  • Cell Image Analysis Techniques
  • Scientific Computing and Data Management
  • Time Series Analysis and Forecasting

Recent publications demonstrate the research focus and collaboration network. Selected recent papers are:

  • "Systems analysis and controlled malaria infection in Europeans and Africans elucidate naturally acquired immunity," 2021, Nature Immunology
  • "Ten Open Challenges in Medical Visualization," 2021, IEEE Computer Graphics and Applications
  • "Class-constrained t-SNE: Combining Data Features and Class Probabilities," 2023, IEEE Transactions on Visualization and Computer Graphics
  • "A Progressive Approach for Uncertainty Visualization in Diffusion Tensor Imaging," 2021, Computer Graphics Forum
  • "ModelWise: Interactive Model Comparison for Model Diagnosis, Improvement and Selection," 2022, Computer Graphics Forum

Anna Vilanova regularly publishes in several venues, with multiple contributions to:

  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Graphics Forum
  • arXiv (Cornell University)
  • IEEE Computer Graphics and Applications
  • bioRxiv (Cold Spring Harbor Laboratory)

Their frequent co-authors include:

  • Maxime Chamberland
  • Stef van den Elzen
  • Thomas Höllt
  • Elmar Eisemann
  • Nicola Pezzotti

Best Publications

  • Approximated and User Steerable tSNE for Progressive Visual Analytics

    Nicola Pezzotti;Boudewijn P. F. Lelieveldt;Laurens van der Maaten;Thomas Hollt

  • Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types

    Vincent van Unen;Thomas Höllt;Thomas Höllt;Nicola Pezzotti;Na Li

  • Evaluation of fiber clustering methods for diffusion tensor imaging

    B. Moberts;A. Vilanova;J.J. van Wijk

  • DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks

    Nicola Pezzotti;Thomas Hollt;Jan Van Gemert;Boudewijn P.F. Lelieveldt

  • Histological validation of high-resolution DTI in human post mortem tissue

    Arne Seehaus;Alard Roebroeck;Matteo Bastiani;Lúcia Fonseca

  • Hierarchical stochastic neighbor embedding

    N. Pezzotti;T. Höllt;B. Lelieveldt;E. Eisemann

  • Structural and Resting State Functional Connectivity of the Subthalamic Nucleus: Identification of Motor STN Parts and the Hyperdirect Pathway

    Ellen Johanna Leonarda Brunenberg;Pim Moeskops;Walter H. Backes;Claudio Pollo;Claudio Pollo

  • Cytosplore: Interactive Immune Cell Phenotyping for Large Single-Cell Datasets

    T. Höllt;N. Pezzotti;V. van Unen;F. Koning

  • An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications.

    Anna Vilanova;Song Zhang;Gordon L. Kindlmann;David H. Laidlaw

  • An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications

    A. Vilanova;S. Zhang;G. Kindlmann;D.H. Laidlaw

  • Automatic Detection of Pulmonary Embolism in CTA Images

    H. Bouma;J.J. Sonnemans;A. Vilanova;F.A. Gerritsen

  • DTI visualization with streamsurfaces and evenly-spaced volume seeding

    A. Vilanova;G. Berenschot;C. van Pul

  • Exploration of 4D MRI Blood Flow using Stylistic Visualization

    Roy van Pelt;Javier Oliván Bescós;Marcel Breeuwer;Rachel E Clough

  • A robust level-set algorithm for centerline extraction

    Alexandru Telea;Anna Vilanova

  • Automating transfer function design for volume rendering using hierarchical clustering of material boundaries

    Petr Šereda;Anna Vilanova;Frans A. Gerritsen

  • Parameter Sensitivity Visualization for DTI Fiber Tracking

    R. Brecheisen;A. Vilanova;B. Platel;B. ter Haar Romeny

  • A method for the quantification of the pressure dependent 3D collagen configuration in the arterial adventitia

    J.T.C. Schrauwen;A. Vilanova;R. Rezakhaniha;N. Stergiopulos

  • Evaluation of Fiber Clustering Methods for Diffusion Tensor Imaging

    Unknown

  • Automatic trajectory planning for deep brain stimulation: a feasibility study

    Ellen J. L. Brunenberg;Anna Vilanova;Veerle Visser-Vandewalle;Yasin Temel

  • Optimizing GPU volume rendering

    Daniel Ruijters;Anna Vilanova

  • CoViCAD: Comprehensive Visualization of Coronary Artery Disease

    M. Termeer;J.O. Bescos;M. Breeuwer;A. Vilanova

  • Interactive Virtual Probing of 4D MRI Blood-Flow

    R. van Pelt;Javier Olivan Bescos;M. Breeuwer;R. E. Clough

Frequent Co-Authors

Elmar Eisemann
Elmar Eisemann Delft University of Technology
Boudewijn P. F. Lelieveldt
Boudewijn P. F. Lelieveldt Leiden University Medical Center
Bart M. ter Haar Romeny
Bart M. ter Haar Romeny Eindhoven University of Technology
Bernhard Preim
Bernhard Preim Otto-von-Guericke University Magdeburg
Frits Koning
Frits Koning Leiden University Medical Center
Alard Roebroeck
Alard Roebroeck Maastricht University
Gordon Kindlmann
Gordon Kindlmann University of Chicago
Helwig Hauser
Helwig Hauser University of Bergen
Maxime Descoteaux
Maxime Descoteaux Université de Sherbrooke
Marcel J. T. Reinders
Marcel J. T. Reinders Delft University of Technology

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