World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
25547
World Ranking
5464
National Ranking
2494

Aleix M. Martinez 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 Aleix M. Martinez 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: 166 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Aleix M. Martinez 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 Aleix M. Martinez 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Aleix M. Martinez is affiliated with The Ohio State University in the United States. Their primary field of study is Computer Science with a focus on several subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology, Computer Graphics and Computer-Aided Design, and Cognitive Neuroscience.

The scientist's research spans various topics, notably:

  • Generative Adversarial Networks and Image Synthesis
  • Digital Media Forensic Detection
  • AI in cancer detection
  • Image Retrieval and Classification Techniques
  • Computer Graphics and Visualization Techniques
  • Advanced Neural Network Applications
  • Advanced Image Processing Techniques

Among recent significant publications by Aleix M. Martinez are:

  • "When do GANs replicate? On the choice of dataset size," 2021, published in the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Characterization of microglia behaviour in healthy and pathological conditions with image analysis tools," 2023, published in Open Biology
  • "Detail Me More: Improving GAN's photo-realism of complex scenes," 2021, published in the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "A fully automatic framework for evaluating cosmetic results of breast conserving therapy," 2022, published in Machine Learning with Applications
  • "The influence of spatial location on same-different judgments of facial identity and expression," 2020, published in Journal of Experimental Psychology Human Perception & Performance

Frequent publication venues for this researcher include:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Open Biology
  • Machine Learning with Applications
  • Journal of Experimental Psychology Human Perception & Performance

Collaborations are a regular part of their work, with frequent coauthors such as:

  • Qianli Feng
  • Fabian Benitez-Quiroz
  • Raghudeep Gadde
  • Chenqi Guo
  • Stuart Synakowski

Best Publications

  • The AR Face Database: CVC Technical Report, 24

    Aleix Martinez;Robert Benavente

  • The AR face database

    A. M. Martinez

  • PCA versus LDA

    A.M. Martinez;A.C. Kak

  • Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements:

    Lisa Feldman Barrett;Ralph Adolphs;Stacy Marsella;Stacy Marsella;Aleix M. Martinez

  • Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class

    A.M. Martinez

  • Compound facial expressions of emotion.

    Shichuan Du;Yong Tao;Aleix M. Martinez

  • EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild

    C. Fabian Benitez-Quiroz;Ramprakash Srinivasan;Aleix M. Martinez

  • GANimation: anatomically-aware facial animation from a single image

    Albert Pumarola;Antonio Agudo;Aleix M. Martinez;Alberto Sanfeliu

  • Subclass discriminant analysis

    Manli Zhu;A.M. Martinez

  • A model of the perception of facial expressions of emotion by humans: research overview and perspectives

    Aleix Martinez;Shichuan Du

  • Where are linear feature extraction methods applicable

    A.M. Martinez;Manli Zhu

  • Computing Smooth Time Trajectories for Camera and Deformable Shape in Structure from Motion with Occlusion

    P. F. U. Gotardo;A. M. Martinez

  • Bayes Optimality in Linear Discriminant Analysis

    O.C. Hamsici;A.M. Martinez

  • Features versus Context: An Approach for Precise and Detailed Detection and Delineation of Faces and Facial Features

    Liya Ding;Aleix M Martinez

  • Support Vector Machines in face recognition with occlusions

    Hongjun Jia;Aleix M Martinez

  • Robust motion estimation under varying illumination

    Yeon-Ho Kim;Aleix M. Martínez;Avi C. Kak

  • Kernel non-rigid structure from motion

    Paulo F. U. Gotardo;Aleix M. Martinez

  • Non-rigid structure from motion with complementary rank-3 spaces

    Paulo F.U. Gotardo;Aleix M. Martinez

  • Emotion perception in emotionless face images suggests a norm-based representation.

    Donald Neth;Aleix M. Martinez

  • Kernel Optimization in Discriminant Analysis

    Di You;O C Hamsici;A M Martinez

Frequent Co-Authors

James T. Todd
James T. Todd The Ohio State University
Sergio Escalera
Sergio Escalera University of Barcelona
Alberto Sanfeliu
Alberto Sanfeliu Universitat Politècnica de Catalunya
Avinash C. Kak
Avinash C. Kak Purdue University West Lafayette
Francesc Moreno-Noguer
Francesc Moreno-Noguer Universitat Politècnica de Catalunya
Stacy Marsella
Stacy Marsella Northeastern University
Ronnie B. Wilbur
Ronnie B. Wilbur Purdue University West Lafayette
Vladimir M. Sloutsky
Vladimir M. Sloutsky The Ohio State University
Seth D. Pollak
Seth D. Pollak University of Wisconsin–Madison
Lisa Feldman Barrett
Lisa Feldman Barrett Northeastern University

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