World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
108
Citations
60712
World Ranking
257
National Ranking
142

Silvio Savarese 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 Silvio Savarese 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: 355 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Silvio Savarese 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 Silvio Savarese 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: 108 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Overview

Silvio Savarese is affiliated with Stanford University in the United States, working primarily in the field of Computer Science. Their research spans several specialized subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Information Systems, and Aerospace Engineering.

The topics that dominate their research include multimodal machine learning applications, natural language processing techniques, robot manipulation and learning, topic modeling, human pose and action recognition, reinforcement learning in robotics, and domain adaptation and few-shot learning.

The scientist has co-authored with several frequent collaborators, including Caiming Xiong, Juan Carlos Niebles, Shelby Heinecke, Roberto Martín-Martín, and Li Fei-Fei.

Silvio Savarese has contributed to numerous publications across various venues with a strong presence in the following outlets:

  • arXiv (Cornell University)
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • The International Journal of Robotics Research

Notable recent papers include:

  • ShapeNet: An Information-Rich 3D Model Repository, 2023, Zenodo (CERN European Organization for Nuclear Research)
  • BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models, 2023, arXiv (Cornell University)
  • Automatic Targetless Extrinsic Calibration of a 3D Lidar and Camera by Maximizing Mutual Information, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis, 2022, arXiv (Cornell University)
  • iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Best Publications

  • Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression

    Hamid Rezatofighi;Nathan Tsoi;JunYoung Gwak;Amir Sadeghian

  • Social LSTM: Human Trajectory Prediction in Crowded Spaces

    Alexandre Alahi;Kratarth Goel;Vignesh Ramanathan;Alexandre Robicquet

  • ShapeNet: An Information-Rich 3D Model Repository

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

  • Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

    Agrim Gupta;Justin Johnson;Li Fei-Fei;Silvio Savarese

  • BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

    Unknown

  • 3D Semantic Parsing of Large-Scale Indoor Spaces

    Iro Armeni;Ozan Sener;Amir R. Zamir;Helen Jiang

  • 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

    Christopher Bongsoo Choy;Danfei Xu;JunYoung Gwak;Kevin Chen

  • Deep Metric Learning via Lifted Structured Feature Embedding

    Hyun Oh Song;Yu Xiang;Stefanie Jegelka;Silvio Savarese

  • 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks

    Christopher Choy;JunYoung Gwak;Silvio Savarese

  • Learning to Track at 100 FPS with Deep Regression Networks

    David Held;Sebastian Thrun;Silvio Savarese

  • Structural-RNN: Deep Learning on Spatio-Temporal Graphs

    Ashesh Jain;Amir R. Zamir;Silvio Savarese;Ashutosh Saxena

  • DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

    Chen Wang;Danfei Xu;Yuke Zhu;Roberto Martin-Martin

  • Active Learning for Convolutional Neural Networks: A Core-Set Approach

    Ozan Sener;Silvio Savarese

  • SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

    Amir Sadeghian;Vineet Kosaraju;Ali Sadeghian;Noriaki Hirose

  • Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes

    Alexandre Robicquet;Amir Sadeghian;Alexandre Alahi;Silvio Savarese

  • Taskonomy: Disentangling Task Transfer Learning

    Amir R. Zamir;Alexander Sax;William Shen;Leonidas Guibas

  • Beyond PASCAL: A benchmark for 3D object detection in the wild

    Yu Xiang;Roozbeh Mottaghi;Silvio Savarese

  • Joint 2D-3D-Semantic Data for Indoor Scene Understanding

    Iro Armeni;Sasha Sax;Amir Roshan Zamir;Silvio Savarese

  • Learning to Track: Online Multi-object Tracking by Decision Making

    Yu Xiang;Alexandre Alahi;Silvio Savarese

  • SEGCloud: Semantic Segmentation of 3D Point Clouds

    Lyne Tchapmi;Christopher Choy;Iro Armeni;JunYoung Gwak

  • Gibson Env: Real-World Perception for Embodied Agents

    Fei Xia;Amir R. Zamir;Zhiyang He;Alexander Sax

  • Taskonomy: Disentangling Task Transfer Learning.

    Amir Roshan Zamir;Amir Roshan Zamir;Alexander Sax;William B. Shen;Leonidas J. Guibas

Frequent Co-Authors

Amir Roshan Zamir
Amir Roshan Zamir Stanford University
Min Sun
Min Sun National Tsing Hua University
Alexandre Alahi
Alexandre Alahi École Polytechnique Fédérale de Lausanne
Li Fei-Fei
Li Fei-Fei Stanford University
Feniosky Peña-Mora
Feniosky Peña-Mora Columbia University
Ashutosh Saxena
Ashutosh Saxena Cornell University
Pietro Perona
Pietro Perona California Institute of Technology
Jitendra Malik
Jitendra Malik University of California, Berkeley
Mani Golparvar-Fard
Mani Golparvar-Fard University of Illinois at Urbana-Champaign
Leonidas J. Guibas
Leonidas J. Guibas Stanford University

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