World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
5992
World Ranking
8936
National Ranking
134

Francisco Casacuberta 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 Francisco Casacuberta 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: 326 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Francisco Casacuberta 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 Francisco Casacuberta 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Francisco Casacuberta is affiliated with the Universitat Politècnica de València in Spain. Their research primarily falls within the field of Computer Science, with a strong focus on Artificial Intelligence. Casacuberta's contributions span multiple subfields, including Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Computational Theory and Mathematics.

The scientist has worked extensively on Natural Language Processing Techniques, which constitute a significant portion of their research output. Other main research topics include Topic Modeling, Text Readability and Simplification, Multimodal Machine Learning Applications, Semantic Web and Ontologies, Handwritten Text Recognition Techniques, and Advanced Text Analysis Techniques.

Casacuberta has coauthored several publications with a range of collaborators. Frequent coauthors include Miguel Domingo, Ángel Navarro, Juan Miguel Vilar, Enrique Vidal, and Salvador Carrión.

They have published articles in various venues. Some of the recurring publication outlets include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Neural Processing Letters
  • Applied Sciences
  • Pattern Recognition Letters

Recent papers authored or coauthored by Casacuberta include:

  • Combining Embeddings of Input Data for Text Classification, 2020, Neural Processing Letters
  • Modernizing Historical Documents: A User Study, 2020, Pattern Recognition Letters
  • Neural Models for Measuring Confidence on Interactive Machine Translation Systems, 2022, Applied Sciences
  • On the Use of Mouse Actions at the Character Level, 2022, Information
  • Interactive Machine Translation for the Language Modernization and Spelling Normalization of Historical Documents, 2023, Pattern Analysis and Applications

This collection of publications reflects a consistent engagement with topics related to machine learning, translation, and historical text processing. Casacuberta's work includes both theoretical approaches and applied methodologies aimed at improving natural language understanding and processing technologies.

Best Publications

  • Probabilistic finite-state machines - part II

    E. Vidal;F. Thollard;C. de la Higuera;F. Casacuberta

  • Statistical approaches to computer-assisted translation

    Sergio Barrachina;Oliver Bender;Francisco Casacuberta;Jorge Civera

  • Machine Translation with Inferred Stochastic Finite-State Transducers

    Francisco Casacuberta;Enrique Vidal

  • INTEGRATED HANDWRITING RECOGNITION AND INTERPRETATION USING FINITE-STATE MODELS

    Alejandro Héctor Toselli;Alfons Juan;Jorge González;Ismael Salvador

  • Topology of strings: median string is NP-complete

    C. de la Higuera;F. Casacuberta

  • Probabilistic finite-state machines - part II

    Unknown

  • The EuTrans Spoken Language Translation System

    Juan Carlos Amengual;Asunción Castaño;Antonio Castellanos;Victor M. Jiménez

  • Some approaches to statistical and finite-state speech-to-speech translation

    F. Casacuberta;H. Ney;F.J. Och;E. Vidal

  • An analysis of general acoustic-phonetic features for Spanish speech produced with the Lombard effect

    Antonio Castellanos;José-Miguel Benedí;Francisco Casacuberta

  • Computational Complexity of Problems on Probabilistic Grammars and Transducers

    Francisco Casacuberta;Colin De La Higuera

  • Online Learning for Interactive Statistical Machine Translation

    Daniel Ortiz-Mart'inez;Ismael Garc'ia-Varea;Francisco Casacuberta

  • Multimodal Interactive Pattern Recognition and Applications

    Alejandro Hctor Toselli;Enrique Vidal;Francisco Casacuberta

  • Interactive neural machine translation

    lvaro Peris;Miguel Domingo;Francisco Casacuberta

  • CASMACAT: An Open Source Workbench for Advanced Computer Aided Translation

    Vicent Alabau;Ragnar Bonk;Christian Buck;Michael Carl

  • Statistical Post-Editing of a Rule-Based Machine Translation System

    Antonio-L. Lagarda;Vicent Alabau;Francisco Casacuberta;Roberto Silva

  • Computer-assisted translation using speech recognition

    E. Vidal;F. Casacuberta;L. Rodriguez;J. Civera

  • Recent efforts in spoken language translation

    F. Casacuberta;M. Federico;H. Ney;E. Vidal

  • Thot: a Toolkit To Train Phrase-based Statistical Translation Models

    Daniel Ortiz-Martínez;Ismael García-Varea;Francisco Casacuberta

  • Local Languages, the Succesor Method, and a Step Towards a General Methodology for the Inference of Regular Grammars

    Pedro Garcia;Enrique Vidal;Francisco Casacuberta

  • Monotone statistical translation using word groups

    Jesús Tomás;Francisco Casacuberta

  • Interactive pattern recognition

    Enrique Vidal;Luis Rodríguez;Francisco Casacuberta;Ismael García-Varea

Frequent Co-Authors

Enrique Vidal
Enrique Vidal Universitat Politècnica de València
Hermann Ney
Hermann Ney RWTH Aachen University
Philipp Koehn
Philipp Koehn Johns Hopkins University
Petia Radeva
Petia Radeva University of Barcelona
Franz Josef Och
Franz Josef Och Google (United States)
Marcello Federico
Marcello Federico Amazon (United States)
Jaime Lloret
Jaime Lloret Universitat Politècnica de València
Gernot A. Fink
Gernot A. Fink TU Dortmund University
Jörg Tiedemann
Jörg Tiedemann University of Helsinki
Gabriele C. Hegerl
Gabriele C. Hegerl University of Edinburgh

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education opens flexible options for those interested in Computer Science and related fields. For students seeking expedited entry into the workforce, consider easy degrees to get online that pay well. These programs typically allow for faster completion and can lead to lucrative roles in IT support, web development, and more.

Specializations are another way to stand out. The growing field of artificial intelligence offers dedicated online AI degree programs. Learn more about available online ai degree programs that combine affordability with industry relevance.

Choosing the right undergraduate focus is key. Explore which program in college aligns best with your career goals, whether it’s computer science, data analytics, or a related discipline.

For those looking to advance their qualifications quickly, there are also easiest masters programs to get into that can boost earning potential and open new tech pathways.

Best Scientists Citing Francisco Casacuberta

Trending Scientists

Recently Published Articles