World's Best Scientists 2026 revealed!
Aude Oliva

Aude Oliva

D-Index & Metrics

Computer Science

D-Index
78
Citations
66830
World Ranking
1160
National Ranking
615

Aude Oliva 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 Aude Oliva 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: 289 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Aude Oliva 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 Aude Oliva 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: 78 D-Index — 92nd percentile

92% 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

  • 2014 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

Aude Oliva is affiliated with MIT in the United States and conducts research primarily in the fields of Computer Science and Neuroscience. Their work spans multiple subfields, including Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence, Sociology and Political Science, and Human-Computer Interaction.

The scientist's research topics cover a range of areas focused on perception, brain function, and machine learning. Key topics include:

  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Neural dynamics and brain function
  • Face Recognition and Perception
  • Visual Attention and Saliency Detection
  • Visual perception and processing mechanisms
  • Anomaly Detection Techniques and Applications

Aude Oliva has published extensively in various venues, with significant contributions to:

  • arXiv (Cornell University)
  • Journal of Vision
  • bioRxiv (Cold Spring Harbor Laboratory)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Among recent publications authored or co-authored by them are:

  • "Ego4D: Around the World in 3,000 Hours of Egocentric Video," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "A M/EEG-fMRI Fusion Primer: Resolving Human Brain Responses in Space and Time," 2020, Neuron
  • "Visual experience is not necessary for the development of face-selectivity in the lateral fusiform gyrus," 2020, Proceedings of the National Academy of Sciences
  • "IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers," 2021, arXiv (Cornell University)
  • "AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Frequent collaborators include Rogério Feris, Rameswar Panda, Camilo Fosco, Benjamin Lahner, and Kate Saenko, reflecting a diverse network engaged in computer vision and related research fields.

In recognition of their work, Aude Oliva was named a Fellow of the John Simon Guggenheim Memorial Foundation in 2014.

Best Publications

  • Learning Deep Features for Discriminative Localization

    Bolei Zhou;Aditya Khosla;Agata Lapedriza;Aude Oliva

  • Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope

    Aude Oliva;Antonio Torralba

  • Places: A 10 Million Image Database for Scene Recognition

    Bolei Zhou;Agata Lapedriza;Aditya Khosla;Aude Oliva

  • SUN database: Large-scale scene recognition from abbey to zoo

    Jianxiong Xiao;James Hays;Krista A. Ehinger;Aude Oliva

  • Learning Deep Features for Scene Recognition using Places Database

    Bolei Zhou;Agata Lapedriza;Jianxiong Xiao;Antonio Torralba

  • Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search.

    Antonio Torralba;Aude Oliva;Monica S. Castelhano;John M. Henderson

  • Building the gist of a scene: the role of global image features in recognition.

    Aude Oliva;Antonio Torralba

  • Visual long-term memory has a massive storage capacity for object details

    Timothy F. Brady;Talia Konkle;George A. Alvarez;Aude Oliva

  • Network Dissection: Quantifying Interpretability of Deep Visual Representations

    David Bau;Bolei Zhou;Aditya Khosla;Aude Oliva

  • The role of context in object recognition

    Aude Oliva;Antonio Torralba

  • A feedforward architecture accounts for rapid categorization

    Thomas Serre;Aude Oliva;Tomaso Poggio

  • Statistics of natural image categories.

    Antonio Torralba;Aude Oliva

  • Object Detectors Emerge in Deep Scene CNNs

    Bolei Zhou;Aditya Khosla;Agata Lapedriza;Aude Oliva

  • Temporal Relational Reasoning in Videos

    Bolei Zhou;Alex Andonian;Aude Oliva;Antonio Torralba

  • From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition

    Philippe G. Schyns;Philippe G. Schyns;Aude Oliva

  • Resolving human object recognition in space and time

    Radoslaw Martin Cichy;Dimitrios Pantazis;Aude Oliva

  • Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

    Radoslaw Martin Cichy;Aditya Khosla;Dimitrios Pantazis;Antonio Torralba

  • What Do Different Evaluation Metrics Tell Us About Saliency Models

    Zoya Bylinskii;Tilke Judd;Aude Oliva;Antonio Torralba

  • What Makes a Visualization Memorable

    Michelle A. Borkin;Azalea A. Vo;Zoya Bylinskii;Phillip Isola

  • Gist of the Scene

    Aude Oliva

  • Top-down control of visual attention in object detection

    A. Oliva;A. Torralba;M.S. Castelhano;J.M. Henderson

Frequent Co-Authors

Bolei Zhou
Bolei Zhou University of California, Los Angeles
George A. Alvarez
George A. Alvarez Harvard University
Jeremy M. Wolfe
Jeremy M. Wolfe Brigham and Women's Hospital
Jianxiong Xiao
Jianxiong Xiao AutoX, Inc.
Hanspeter Pfister
Hanspeter Pfister Harvard University
Philippe G. Schyns
Philippe G. Schyns University of Glasgow

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