World's Best Scientists 2026 revealed!
Fernando Perez-Cruz

Fernando Perez-Cruz

D-Index & Metrics

Computer Science

D-Index
39
Citations
7485
World Ranking
9664
National Ranking
173

Fernando Perez-Cruz 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 Fernando Perez-Cruz 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: 165 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.

Fernando Perez-Cruz 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 Fernando Perez-Cruz 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: 39 D-Index — 33rd percentile

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

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

Overview

Fernando Perez-Cruz is affiliated with ETH Zurich in Switzerland and has a diverse research portfolio primarily in the fields of Computer Science and Engineering. Their work spans multiple subfields including Artificial Intelligence, Civil and Structural Engineering, Computer Vision and Pattern Recognition, Signal Processing, and Global and Planetary Change.

The scientist's research topics focus on areas such as Infrastructure Maintenance and Monitoring, Gaussian Processes and Bayesian Inference, Structural Health Monitoring Techniques, Generative Adversarial Networks and Image Synthesis, Traffic Prediction and Management Techniques, Hydrology and Watershed Management Studies, and Computational Drug Discovery Methods.

Fernando Perez-Cruz has contributed to a number of recent publications, including the following papers:

  • Facilitated machine learning for image-based fruit quality assessment, 2022, Journal of Food Engineering
  • Generating LOD3 building models from structure-from-motion and semantic segmentation, 2022, Automation in Construction
  • Integration and calibration of non-dispersive infrared (NDIR) CO 2 low-cost sensors and their operation in a sensor network covering Switzerland, 2020, Atmospheric Measurement Techniques
  • TOPO-Loss for continuity-preserving crack detection using deep learning, 2022, Construction and Building Materials
  • Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland, 2022, Natural Hazards and Earth System Sciences

The scientist has frequently published in venues such as:

  • arXiv (Cornell University), 25 publications
  • Zenodo (CERN European Organization for Nuclear Research), 11 publications
  • bioRxiv (Cold Spring Harbor Laboratory), 4 publications
  • Repository for Publications and Research Data (ETH Zurich), 3 publications
  • Automation in Construction, 2 publications

Among book contributions, Fernando Perez-Cruz has published three titles with Springer Science+Business Media under the series "Machine Learning and Knowledge Discovery in Databases. Research Track" in 2021, with citation counts of 15, 8, and 3 respectively.

The scientist has collaborated extensively with several co-authors, including:

  • Nathanaël Perraudin, 12 joint publications
  • Lilian Gasser, 9 joint publications
  • Romana Rust, 8 joint publications
  • Gonzalo Casas, 8 joint publications
  • Matthias Köhler, 8 joint publications

Best Publications

  • Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

    Briland Hitaj;Giuseppe Ateniese;Fernando Perez-Cruz

  • Kullback-Leibler divergence estimation of continuous distributions

    F. Perez-Cruz

  • Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation

    D. Tuia;J. Verrelst;L. Alonso;F. Perez-Cruz

  • SVM multiregression for nonlinear channel estimation in multiple-input multiple-output systems

    M. Sanchez-Fernandez;M. de-Prado-Cumplido;J. Arenas-Garcia;F. Perez-Cruz

  • Multi-dimensional function approximation and regression estimation

    Fernando Perez-Cruz;Gustavo Camps-Valls;Emilio Soria-Olivas;Juan José Perez-Ruixo

  • Expectation Propagation Detection for High-Order High-Dimensional MIMO Systems

    Javier Cespedes;Pablo M. Olmos;Matilde Sanchez-Fernandez;Fernando Perez-Cruz

  • Wireless RSSI fingerprinting localization

    Simon Yiu;Marzieh Dashti;Holger Claussen;Fernando Perez-Cruz

  • PassGAN: A Deep Learning Approach for Password Guessing

    Briland Hitaj;Paolo Gasti;Giuseppe Ateniese;Fernando Perez-Cruz

  • MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation

    F. Perez-Cruz;M.R.D. Rodrigues;S. Verdu

  • Joint Source and Channel Coding

    Maria Fresia;Fernando Peréz-Cruz;H Vincent Poor;Sergio Verdú

  • Methods for feature selection in a learning machine

    Jason Aaron Edward Weston;André Elisseeff;Bernhard Schoelkopf;Fernando Pérez-Cruz

  • Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances

    F. Perez-Cruz;S. Van Vaerenbergh;J. JoseMurillo-Fuentes;M. Lazaro-Gredilla

  • Kernel methods and their potential use in signal processing

    F. Perez-Cruz;O. Bousquet

  • Estimating GARCH models using support vector machines

    Fernando Pérez-cruz;Julio A Afonso-rodríguez;Javier Giner

  • Feature selection and transduction for prediction of molecular bioactivity for drug design.

    Jason Weston;Fernando Pérez-Cruz;Olivier Bousquet;Olivier Chapelle

  • Gaussian Processes for Nonlinear Signal Processing

    Fernando Pérez-Cruz;Steven Van Vaerenbergh;Juan José Murillo-Fuentes;Miguel Lázaro-Gredilla

  • Machine learning and data mining: strategies for hypothesis generation

    M A Oquendo;E Baca-Garcia;A Artés-Rodríguez;F Perez-Cruz;F Perez-Cruz

  • Weighted least squares training of support vector classifiers leading to compact and adaptive schemes

    A. Navia-Vazquez;F. Perez-Cruz;A. Artes-Rodriguez;A.R. Figueiras-Vidal

  • An IRWLS procedure for SVR

    F. Perez-Cruz;A. Navia Vazquez;P. L. Alarcon-Diana;A. Artes-Rodriguez

  • Estimation of Information Theoretic Measures for Continuous Random Variables

    Fernando Pérez-Cruz

Frequent Co-Authors

Jason Weston
Jason Weston Facebook (United States)
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Ignacio Santamaria
Ignacio Santamaria University of Cantabria
Sergio Verdu
Sergio Verdu Princeton University
Miguel R. D. Rodrigues
Miguel R. D. Rodrigues University College London
Isabelle Guyon
Isabelle Guyon University of Paris-Saclay
Sancho Salcedo-Sanz
Sancho Salcedo-Sanz University of Alcalá
Giuseppe Ateniese
Giuseppe Ateniese George Mason University
Aníbal R. Figueiras-Vidal
Aníbal R. Figueiras-Vidal Carlos III University of Madrid
Howard Huang
Howard Huang Nokia (United States)

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