World's Best Scientists 2026 revealed!
Miguel Á. Carreira-Perpiñán

Miguel Á. Carreira-Perpiñán

D-Index & Metrics

Computer Science

D-Index
31
Citations
7757
World Ranking
13370
National Ranking
5353

Miguel Á. Carreira-Perpiñán 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 Miguel Á. Carreira-Perpiñán 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: 153 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Miguel Á. Carreira-Perpiñán 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 Miguel Á. Carreira-Perpiñán 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: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Miguel Á. Carreira-Perpiñán is affiliated with the University of California, Merced in the United States. Their research spans multiple areas within computer science, with a primary focus on artificial intelligence and machine learning.

The scientist's work covers several main fields of study including:

  • Computer Science

Within this broad discipline, the subfields that feature prominently in their publications are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Signal Processing

Key topics addressed in their research include:

  • Explainable Artificial Intelligence (XAI)
  • Machine Learning and Data Classification
  • Neural Networks and Applications
  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Formal Methods in Verification
  • Advanced Neural Network Applications

Some of the recent papers authored or coauthored by Miguel Á. Carreira-Perpiñán are:

  • "Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Optimal Interpretable Clustering Using Oblique Decision Trees," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees," 2022, 2022 International Joint Conference on Neural Networks (IJCNN)
  • "Sparse oblique decision trees: a tool to understand and manipulate neural net features," 2023, Data Mining and Knowledge Discovery

The scientist has frequently collaborated with several coauthors, including:

  • Suryabhan Singh Hada
  • Magzhan Gabidolla
  • Yerlan Idelbayev
  • Arman Zharmagambetov
  • Alberto Cerpa

Their publications have appeared in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 International Joint Conference on Neural Networks (IJCNN)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Best Publications

  • Multiscale conditional random fields for image labeling

    Xuming He;R.S. Zemel;M.A. Carreira-Perpinan

  • On Contrastive Divergence Learning.

    Miguel Á. Carreira-Perpiñán;Geoffrey E. Hinton

  • A Review of Dimension Reduction Techniques

    Miguel Á. Carreira-Perpiñán

  • Non-rigid point set registration: Coherent Point Drift

    Andriy Myronenko;Xubo Song;Miguel Á. Carreira-Perpiñán

  • OBSERVE: Occupancy-based system for efficient reduction of HVAC energy

    Varick L. Erickson;Miguel A. Carreira-Perpinan;Alberto E. Cerpa

  • Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application

    Weiran Wang;Miguel Á. Carreira-Perpiñán

  • Mode-finding for mixtures of Gaussian distributions

    M.A. Carreira-Perpinan

  • Gaussian Mean-Shift Is an EM Algorithm

    M.A. Carreira-Perpinan

  • Constrained spectral clustering through affinity propagation

    Zhengdong Lu;M.A. Carreira-Perpinan

  • "Learning-Compression" Algorithms for Neural Net Pruning

    Miguel A. Carreira-Perpinan;Yerlan Idelbayev

  • Hashing with binary autoencoders

    Miguel A. Carreira-Perpinan;Ramin Raziperchikolaei

  • Occupancy Modeling and Prediction for Building Energy Management

    Varick L. Erickson;Miguel Á. Carreira-Perpiñán;Alberto E. Cerpa

  • Proximity Graphs for Clustering and Manifold Learning

    Richard S. Zemel;Miguel Á. Carreira-Perpiñán

  • Distributed optimization of deeply nested systems

    Miguel Á. Carreira-Perpiñán;Weiran Wang

  • Fast nonparametric clustering with Gaussian blurring mean-shift

    Miguel Á. Carreira-Perpiñán

  • The elastic embedding algorithm for dimensionality reduction

    Miguel Á. Carreira-Perpiñan

  • Acceleration Strategies for Gaussian Mean-Shift Image Segmentation

    M.A. Carreira-Perpinan

  • On the number of modes of a Gaussian mixture

    Miguel Á. Carreira-Perpiñán;Christopher K. I. Williams

  • A review of mean-shift algorithms for clustering.

    Miguel Á. Carreira-Perpiñán

  • Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions

    Miguel Á. Carreira-Perpiñán;Steve Á. Renals

  • Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer

    Yerlan Idelbayev;Miguel A. Carreira-Perpinan

Frequent Co-Authors

Zhengdong Lu
Zhengdong Lu Huawei Technologies (China)
Geoffrey J. Goodhill
Geoffrey J. Goodhill Washington University in St. Louis
Steve Renals
Steve Renals University of Edinburgh
Robert Wang
Robert Wang Chinese Academy of Sciences
Mark Sandler
Mark Sandler Google (United States)
Richard S. Zemel
Richard S. Zemel University of Toronto
Deniz Erdogmus
Deniz Erdogmus Northeastern University
Dominic W. Massaro
Dominic W. Massaro University of California, Santa Cruz
Cristian Sminchisescu
Cristian Sminchisescu Google (United States)
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto

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