World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
21832
World Ranking
6641
National Ranking
2934

Oncel Tuzel 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 Oncel Tuzel 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: 140 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Oncel Tuzel 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 Oncel Tuzel 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Oncel Tuzel is a researcher affiliated with Apple in the United States, specializing in computer science with a significant focus on computer vision and related areas. Their academic contributions span several subfields, including computer vision and pattern recognition, artificial intelligence, signal processing, industrial and manufacturing engineering, and computational mechanics.

Tuzel's work is primarily concentrated in the following topics:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Music and Audio Processing
  • Multimodal Machine Learning Applications
  • Speech Recognition and Synthesis
  • Advanced Image and Video Retrieval Techniques
  • Natural Language Processing Techniques

Their frequent co-authors include Hadi Pouransari, Jen-Hao Rick Chang, Fartash Faghri, Raviteja Vemulapalli, and Pavan Kumar Anasosalu Vasu, indicating collaborative work predominantly within computer vision and machine learning research communities.

Tuzel has published extensively, with 130 publications mainly appearing in:

  • arXiv (Cornell University) - 51 publications
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - 2 publications
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) - 1 publication
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - 1 publication
  • 2021 29th European Signal Processing Conference (EUSIPCO) - 1 publication

Some recent papers that feature the breadth of their research work include:

  • "Subject-Aware Contrastive Learning for Biosignals," 2020, arXiv (Cornell University)
  • "FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization," 2023, arXiv (Cornell University)
  • "GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models," 2024, arXiv (Cornell University)
  • "Token Pooling in Vision Transformers for Image Classification," 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "SYNT++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Best Publications

  • VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

    Yin Zhou;Oncel Tuzel

  • Region Covariance : A Fast Descriptor for Detection and Classification

    Oncel Tuzel;Fatih Porikli;Peter Meer

  • Learning from Simulated and Unsupervised Images through Adversarial Training

    Ashish Shrivastava;Tomas Pfister;Oncel Tuzel;Joshua Susskind

  • Coupled Generative Adversarial Networks

    Ming-Yu Liu;Oncel Tuzel

  • Pedestrian Detection via Classification on Riemannian Manifolds

    O. Tuzel;F. Porikli;P. Meer

  • Entropy rate superpixel segmentation

    Ming-Yu Liu;Oncel Tuzel;Srikumar Ramalingam;Rama Chellappa

  • Covariance Tracking using Model Update Based on Lie Algebra

    F. Porikli;O. Tuzel;P. Meer

  • Human Detection via Classification on Riemannian Manifolds

    O. Tuzel;F. Porikli;P. Meer

  • A Multi-stream Bi-directional Recurrent Neural Network for Fine-Grained Action Detection

    Bharat Singh;Tim K. Marks;Michael Jones;Oncel Tuzel

  • R-CNN for Small Object Detection

    Chenyi Chen;Ming-Yu Liu;Oncel Tuzel;Jianxiong Xiao

  • MVX-Net: Multimodal VoxelNet for 3D Object Detection

    Vishwanath A. Sindagi;Yin Zhou;Oncel Tuzel

  • MobileOne: An Improved One millisecond Mobile Backbone

    Unknown

  • Joint Geodesic Upsampling of Depth Images

    Ming-Yu Liu;Oncel Tuzel;Yuichi Taguchi

  • Fast directional chamfer matching

    Ming-Yu Liu;Oncel Tuzel;Ashok Veeraraghavan;Rama Chellappa

  • Fast object localization and pose estimation in heavy clutter for robotic bin picking

    Ming-Yu Liu;Ming-Yu Liu;Oncel Tuzel;Ashok Veeraraghavan;Ashok Veeraraghavan;Yuichi Taguchi

  • Voting-based pose estimation for robotic assembly using a 3D sensor

    Changhyun Choi;Yuichi Taguchi;Oncel Tuzel;Ming-Yu Liu

  • Human Body Tracking by Adaptive Background Models and Mean-Shift Analysis

    Fatih Porikli;Oncel Tuzel

  • Semi-Supervised Kernel Mean Shift Clustering

    Saket Anand;Sushil Mittal;Oncel Tuzel;Peter Meer

  • Gaussian Conditional Random Field Network for Semantic Segmentation

    Raviteja Vemulapalli;Oncel Tuzel;Ming-Yu Liu;Rama Chellappa

  • Entropy-Rate Clustering: Cluster Analysis via Maximizing a Submodular Function Subject to a Matroid Constraint

    Ming-Yu Liu;Oncel Tuzel;Srikumar Ramalingam;Rama Chellappa

  • Deep hierarchical parsing for semantic segmentation

    Abhishek Sharma;Oncel Tuzel;David W. Jacobs

Frequent Co-Authors

Ming-Yu Liu
Ming-Yu Liu Nvidia (United States)
Fatih Porikli
Fatih Porikli Australian National University
Peter Meer
Peter Meer Rutgers, The State University of New Jersey
Ashok Veeraraghavan
Ashok Veeraraghavan Rice University
Rama Chellappa
Rama Chellappa Johns Hopkins University
Aswin C. Sankaranarayanan
Aswin C. Sankaranarayanan Carnegie Mellon University
Michael Jones
Michael Jones Mitsubishi Electric (United States)
Lin Yang
Lin Yang University of Florida
David W. Jacobs
David W. Jacobs University of Maryland, College Park

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