World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
13934
World Ranking
5011
National Ranking
2329

Ingo Wald 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 Ingo Wald 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: 169 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Ingo Wald 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 Ingo Wald 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

Ingo Wald is affiliated with Nvidia in the United States and has contributed extensively to the fields of computer science and engineering. Their research primarily focuses on computer graphics and visualization techniques, with additional work in computer vision, computational mechanics, and related areas.

Their published work encompasses a variety of topics including computer graphics and visualization techniques, 3D shape modeling and analysis, computational geometry and mesh generation, advanced vision and imaging, remote sensing and LiDAR applications, data management and algorithms, and advanced data storage technologies.

Frequent publication venues for Ingo Wald include:

  • arXiv (Cornell University)
  • Computer Graphics Forum
  • IEEE Transactions on Visualization and Computer Graphics
  • Computing in Science & Engineering
  • Proceedings of the ACM on Computer Graphics and Interactive Techniques

Their significant recent papers illustrate a range of topics within visualization and computational methods:

  • "A terminology for in situ visualization and analysis systems," 2020, The International Journal of High Performance Computing Applications
  • "An GPU-accelerated particle tracking method for Eulerian-Lagrangian simulations using hardware ray tracing cores," 2021, Computer Physics Communications
  • "Accelerating Unstructured Mesh Point Location With RT Cores," 2020, IEEE Transactions on Visualization and Computer Graphics
  • "State-of-the-art in Large-Scale Volume Visualization Beyond Structured Data," 2023, Computer Graphics Forum
  • "Quick Clusters: A GPU-Parallel Partitioning for Efficient Path Tracing of Unstructured Volumetric Grids," 2022, IEEE Transactions on Visualization and Computer Graphics

Ingo Wald frequently collaborates with several co-authors. Notable collaborators include Stefan Zellmann, Valerio Pascucci, Will Usher, Nate Morrical, and Uğur Güdükbay.

Best Publications

  • Parallel & distributed processing

    Philipp Slusallek;Peter Shirley;William Mark;Gordon Stoll

  • Realtime Ray Tracing and Interactive Global Illumination

    Ingo Wald

  • On building fast kd-Trees for Ray Tracing, and on doing that in O(N log N)

    Ingo Wald;Vlastimil Havran

  • Interactive Rendering with Coherent Ray Tracing

    Unknown

  • Ray tracing deformable scenes using dynamic bounding volume hierarchies

    Ingo Wald;Solomon Boulos;Peter Shirley

  • Embree: a kernel framework for efficient CPU ray tracing

    Ingo Wald;Sven Woop;Carsten Benthin;Gregory S. Johnson

  • State of the Art in Ray Tracing Animated Scenes

    Ingo Wald;Ingo Wald;William R. Mark;William R. Mark;Johannes Günther;Solomon Boulos;Solomon Boulos

  • On fast Construction of SAH-based Bounding Volume Hierarchies

    I. Wald

  • Ray tracing animated scenes using coherent grid traversal

    Ingo Wald;Thiago Ize;Andrew Kensler;Aaron Knoll

  • Interactive Global Illumination

    Ingo Wald;Thomas Kollig;Carsten Benthin;Alexander Keller

  • Interactive global illumination using fast ray tracing

    Ingo Wald;Thomas Kollig;Carsten Benthin;Alexander Keller

  • Interactive Distributed Ray Tracing of Highly Complex Models

    Ingo Wald;Philipp Slusallek;Carsten Benthin;Markus Wagner

  • SaarCOR: a hardware architecture for ray tracing

    Jörg Schmittler;Ingo Wald;Philipp Slusallek

  • An interactive out-of-core rendering framework for visualizing massively complex models

    Ingo Wald;Andreas Dietrich;Philipp Slusallek

  • Ray Tracing on the Cell Processor

    C. Benthin;I. Wald;M. Scherbaum;H. Friedrich

  • OSPRay - A CPU Ray Tracing Framework for Scientific Visualization

    I Wald;GP Johnson;J Amstutz;C Brownlee

  • State of the Art in Interactive Ray Tracing

    Ingo Wald;Philipp Slusallek

  • Distributed interactive ray tracing of dynamic scenes

    I. Wald;C. Benthin;P. Slusallek

  • Realtime Ray Tracing and its use for Interactive Global Illumination

    Ingo Wald;Timothy J. Purcell;Jörg Schmittler;Carsten Benthin

  • Packet-based whitted and distribution ray tracing

    Solomon Boulos;Dave Edwards;J. Dylan Lacewell;Joe Kniss

  • Introduction to real-time ray tracing

    Philipp Slusallek;Peter Shirley;William Mark;Gordon Stoll

Frequent Co-Authors

Philipp Slusallek
Philipp Slusallek Saarland University
Steven G. Parker
Steven G. Parker Nvidia (United States)
Valerio Pascucci
Valerio Pascucci University of Utah
Peter Shirley
Peter Shirley Nvidia (United States)
Hans-Peter Seidel
Hans-Peter Seidel Max Planck Institute for Informatics
William R. Mark
William R. Mark Google (United States)
Charles Hansen
Charles Hansen University of Utah
Chris R. Johnson
Chris R. Johnson University of Utah
Alexander Keller
Alexander Keller Nvidia (United States)
Hans Hagen
Hans Hagen Technical University of Kaiserslautern

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