World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
99
Citations
48435
World Ranking
386
National Ranking
213

Thomas Funkhouser 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 Thomas Funkhouser 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: 202 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Thomas Funkhouser 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 Thomas Funkhouser 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: 99 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2018 - ACM Fellow For research contributions in computer graphics
  • 1999 - Fellow of Alfred P. Sloan Foundation

Overview

Thomas Funkhouser is affiliated with Google in the United States and has a substantial body of research primarily in computer science and engineering. Their work spans multiple subfields, including computer vision and pattern recognition, computer graphics and computer-aided design, computational mechanics, control and systems engineering, and artificial intelligence.

Funkhouser's research topics cover a range of advanced technical areas. These include:

  • Computer Graphics and Visualization Techniques
  • 3D Shape Modeling and Analysis
  • Advanced Vision and Imaging
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Robot Manipulation and Learning
  • Robotics and Sensor-Based Localization

The scientist has contributed numerous papers to highly regarded publication venues. Frequent venues where they have published include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Robotics and Automation Letters
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Zenodo (CERN European Organization for Nuclear Research)

Some of their recent papers are:

  • "ShapeNet: An Information-Rich 3D Model Repository," 2023, Zenodo (CERN European Organization for Nuclear Research)
  • "TossingBot: Learning to Throw Arbitrary Objects With Residual Physics," 2020, IEEE Transactions on Robotics
  • "Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Grasping in the Wild: Learning 6DoF Closed-Loop Grasping From Low-Cost Demonstrations," 2020, IEEE Robotics and Automation Letters
  • "TidyBot: personalized robot assistance with large language models," 2023, Autonomous Robots

Collaboration is a notable aspect of Funkhouser's career. Frequent co-authors include:

  • Kyle Genova
  • Abhijit Kundu
  • Alireza Fathi
  • Shuran Song
  • Caroline Pantofaru

Funkhouser has received recognition in their field, having been named an ACM Fellow in 2018 for research contributions in computer graphics. Earlier in their career, they were honored as a Fellow of the Alfred P. Sloan Foundation in 1999.

Best Publications

  • ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes

    Angela Dai;Angel X. Chang;Manolis Savva;Maciej Halber

  • Shape distributions

    Robert Osada;Thomas Funkhouser;Bernard Chazelle;David Dobkin

  • ShapeNet: An Information-Rich 3D Model Repository

    Angel X. Chang;Thomas A. Funkhouser;Leonidas J. Guibas;Pat Hanrahan

  • The Princeton Shape Benchmark

    P. Shilane;P. Min;M. Kazhdan;T. Funkhouser

  • Rotation invariant spherical harmonic representation of 3D shape descriptors

    Michael Kazhdan;Thomas Funkhouser;Szymon Rusinkiewicz

  • Dilated Residual Networks

    Fisher Yu;Vladlen Koltun;Thomas Funkhouser

  • Matterport3D: Learning from RGB-D Data in Indoor Environments

    Angel Chang;Angela Dai;Thomas Funkhouser;Maciej Halber

  • A search engine for 3D models

    Thomas Funkhouser;Patrick Min;Michael Kazhdan;Joyce Chen

  • Semantic Scene Completion from a Single Depth Image

    Shuran Song;Fisher Yu;Andy Zeng;Angel X. Chang

  • 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

    Andy Zeng;Shuran Song;Matthias NieBner;Matthew Fisher

  • Adaptive display algorithm for interactive frame rates during visualization of complex virtual environments

    Thomas A. Funkhouser;Carlo H. Séquin

  • Matching 3D models with shape distributions

    R. Osada;T. Funkhouser;B. Chazelle;D. Dobkin;D. Dobkin

  • ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes

    Angela Dai;Angel X. Chang;Manolis Savva;Maciej Halber

  • A benchmark for 3D mesh segmentation

    Xiaobai Chen;Aleksey Golovinskiy;Thomas Funkhouser

  • Modeling by example

    Thomas Funkhouser;Michael Kazhdan;Philip Shilane;Patrick Min

  • IBRNet: Learning Multi-View Image-Based Rendering

    Qianqian Wang;Zhicheng Wang;Kyle Genova;Pratul Srinivasan

  • Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning

    Andy Zeng;Shuran Song;Stefan Welker;Johnny Lee

  • Shape-based recognition of 3D point clouds in urban environments

    Aleksey Golovinskiy;Vladimir G. Kim;Thomas Funkhouser

  • Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching

    Andy Zeng;Shuran Song;Kuan-Ting Yu;Elliott Donlon

  • Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    John A. Capra;Roman A. Laskowski;Janet M. Thornton;Mona Singh

  • 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

    Andy Zeng;Shuran Song;Matthias Nießner;Matthew Fisher

  • Local Implicit Grid Representations for 3D Scenes

    Chiyu Max Jiang;Avneesh Sud;Ameesh Makadia;Jingwei Huang

Frequent Co-Authors

Shuran Song
Shuran Song Stanford University
Szymon Rusinkiewicz
Szymon Rusinkiewicz Princeton University
Michael Kazhdan
Michael Kazhdan Johns Hopkins University
Manolis Savva
Manolis Savva Simon Fraser University
Yinda Zhang
Yinda Zhang Google (United States)
Angel X. Chang
Angel X. Chang Simon Fraser University
Vladimir G. Kim
Vladimir G. Kim Adobe Systems (United States)
Yaron Lipman
Yaron Lipman Facebook (United States)
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Adam Finkelstein
Adam Finkelstein Princeton University

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