World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
48
Citations
8330
World Ranking
4607
National Ranking
102

Elías Cueto publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Elías Cueto sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 294 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Elías Cueto D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Elías Cueto sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 48 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Elías Cueto is affiliated with the University of Zaragoza in Spain and has contributed extensively to research in engineering, computer science, and physics and astronomy. Their scholarly work spans multiple subfields, including statistical and nonlinear physics, artificial intelligence, computational theory and mathematics, computer vision and pattern recognition, and statistics, probability, and uncertainty.

Their research focuses on several main topics: model reduction and neural networks, probabilistic and robust engineering design, neural networks and applications, real-time simulation and control systems, machine learning in materials science, modeling and simulation systems, and advanced thermodynamics and statistical mechanics.

Elías Cueto has published papers in a variety of venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Jornadas de jóvenes investigadores del I3A
  • Computer Methods in Applied Mechanics and Engineering
  • Advanced Modeling and Simulation in Engineering Sciences
  • Computational Mechanics

Among their recent papers are:

  • Deep learning of thermodynamics-aware reduced-order models from data (2021), published in Computer Methods in Applied Mechanics and Engineering
  • From ROM of Electrochemistry to AI-Based Battery Digital and Hybrid Twin (2020), published in Archives of Computational Methods in Engineering
  • Structure-preserving neural networks (2020), published in Journal of Computational Physics
  • Digital twins that learn and correct themselves (2020), published in International Journal for Numerical Methods in Engineering
  • Thermodynamics-Informed Graph Neural Networks (2022), published in IEEE Transactions on Artificial Intelligence

Frequent coauthors who have collaborated with Elías Cueto include:

  • Francisco Chinesta
  • David González
  • Icíar Alfaro
  • Victor Champaney
  • Chady Ghnatios

The scientist has contributed to the publishing of at least one book through Springer International Publishing, titled A Gentle Introduction to Data, Learning, and Model Order Reduction, which is expected in 2025.

Best Publications

  • A Short Review on Model Order Reduction Based on Proper Generalized Decomposition

    Francisco Chinesta;Pierre Ladeveze;Elías Cueto

  • Recent Advances and New Challenges in the Use of the Proper Generalized Decomposition for Solving Multidimensional Models

    Francisco Chinesta;Amine Ammar;Elías Cueto

  • PGD-Based Computational Vademecum for Efficient Design, Optimization and Control

    Francisco Chinesta;Adrien Leygue;Felipe Bordeu;Jose Vicente Aguado

  • Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data

    Francisco Chinesta;Elías G. Cueto;Emmanuelle Abisset-Chavanne;Jean Louis Duval

  • A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

    Rubén Ibañez;Emmanuelle Abisset-Chavanne;Jose Vicente Aguado;David Gonzalez

  • Overview and recent advances in natural neighbour galerkin methods

    E. Cueto;N. Sukumar;B. Calvo;M. A. Martínez

  • On the "a priori" model reduction: overview and recent developments

    David Ryckelynck;Francisco Chinesta;Elías Cueto;Amine Ammar

  • Recent advances on the use of separated representations

    David González;Amine Ammar;Francisco Chinesta;Elías Cueto

  • Real-time deformable models of non-linear tissues by model reduction techniques

    S. Niroomandi;I. Alfaro;E. Cueto;F. Chinesta

  • Data-driven non-linear elasticity: constitutive manifold construction and problem discretization

    Ruben Ibañez;Domenico Borzacchiello;Jose Vicente Aguado;Emmanuelle Abisset-Chavanne

  • Imposing essential boundary conditions in the natural element method by means of density-scaled?-shapes

    E. Cueto;M. Doblaré;L. Gracia

  • Proper Generalized Decomposition based dynamic data-driven control of thermal processes ☆

    Chady Ghnatios;Françoise Masson;Antonio Huerta;Adrien Leygue

  • Proper generalized decomposition of time-multiscale models

    Amine Ammar;Francisco Chinesta;Elías Cueto;Manuel Doblaré

  • Real-time simulation of biological soft tissues: a PGD approach

    S. Niroomandi;D. González;I. Alfaro;F. Bordeu

  • Parametric solutions involving geometry: A step towards efficient shape optimization

    Amine Ammar;Antonio Huerta;Antonio Huerta;Francisco Chinesta;Elías Cueto

  • On the employ of meshless methods in biomechanics

    M. Doblaré;E. Cueto;B. Calvo;M.A. Martínez

  • Accounting for large deformations in real-time simulations of soft tissues based on reduced-order models

    S. Niroomandi;I. Alfaro;E. Cueto;F. Chinesta

  • Thermodynamically consistent data-driven computational mechanics

    David González;Francisco Chinesta;Elías Cueto

  • Model order reduction for hyperelastic materials

    Siamak Niroomandi;Icíar Alfaro;Elías Cueto;Francisco Chinesta

  • Non incremental strategies based on separated representations: applications in computational rheology

    Amine Ammar;M. Normandin;F. Daim;D. Gonzalez

Frequent Co-Authors

Manuel Doblaré
Manuel Doblaré University of Zaragoza
Antonio Huerta
Antonio Huerta Universitat Politècnica de Catalunya
Luigino Filice
Luigino Filice University of Calabria
Julien Yvonnet
Julien Yvonnet Gustave Eiffel University
Roland Keunings
Roland Keunings Université Catholique de Louvain
Miguel Ángel Martínez
Miguel Ángel Martínez University of Zaragoza
Malcolm R. Mackley
Malcolm R. Mackley University of Cambridge
Begoña Calvo
Begoña Calvo University of Zaragoza
Jean-Michel Bergheau
Jean-Michel Bergheau École Nationale d'Ingénieurs de Saint-Étienne

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