World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
13586
World Ranking
3820
National Ranking
231

Anna Korhonen 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 Anna Korhonen 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 243 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Anna Korhonen 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 Anna Korhonen sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Anna Korhonen is affiliated with the University of Cambridge in the United Kingdom and specializes in the field of computer science, with a strong focus on artificial intelligence. Their research extends into several subfields including computer vision and pattern recognition, molecular biology, hardware and architecture, and radiology, nuclear medicine, and imaging.

The scientist's work spans multiple main topics within their discipline, notably:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Speech and Dialogue Systems
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Domain Adaptation and Few-Shot Learning
  • Biomedical Text Mining and Ontologies

Anna Korhonen has published extensively, with a significant number of articles appearing in venues such as arXiv (Cornell University), Transactions of the Association for Computational Linguistics, Apollo (University of Cambridge), the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, and the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Long Papers).

Among recent published papers, the following stand out with details of publication year and venue:

  • Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans, 2020, Research Portal (King's College London)
  • A systematic literature review of automatic Alzheimer's disease detection from speech and language, 2020, Journal of the American Medical Informatics Association
  • Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • The impact of imputation quality on machine learning classifiers for datasets with missing values, 2023, Communications Medicine
  • Composable Sparse Fine-Tuning for Cross-Lingual Transfer, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Frequent collaborators in their research include:

  • Ivan Vulić
  • Edoardo Maria Ponti
  • Nigel Collier
  • Roi Reichart
  • Simon Baker

The research portfolio of Anna Korhonen reflects significant engagement in interdisciplinary applications of machine learning, particularly relating to biomedical domains and language processing. Their body of work contributes to advancing computational methods in artificial intelligence with implications across speech systems, multilingual transfer learning, and medical data analysis.

Best Publications

  • Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

    Michael Roberts;Michael Roberts;Derek Driggs;Matthew Thorpe;Julian D. Gilbey

  • Simlex-999: Evaluating semantic models with genuine similarity estimation

    Felix Hill;Roi Reichart;Anna Korhonen

  • Learning distributed representations of sentences from unlabelled data

    Felix Hill;Kyunghyun Cho;Anna Korhonen

  • A large-scale classification of English verbs

    Karin Kipper;Anna Korhonen;Neville Ryant;Martha Palmer

  • How to Train good Word Embeddings for Biomedical NLP

    Billy Chiu;Gamal K. O. Crichton;Anna Korhonen;Sampo Pyysalo

  • Extending VerbNet with Novel Verb Classes

    Karin Kipper;Anna Korhonen;Neville Ryant;Martha Palmer

  • SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity

    Daniela Gerz;Ivan Vulic;Felix Hill;Roi Reichart

  • A neural network multi-task learning approach to biomedical named entity recognition

    Gamal K. O. Crichton;Sampo Pyysalo;Billy Chiu;Anna Korhonen

  • Metaphor Identification Using Verb and Noun Clustering

    Ekaterina Shutova;Lin Sun;Anna Korhonen

  • Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrksic;Nikola Mrksic;Ivan Vulic;Diarmuid Ó Séaghdha;Ira Leviant

  • Probing Pretrained Language Models for Lexical Semantics

    Ivan Vulić;Edoardo Maria Ponti;Robert Litschko;Goran Glavaš

  • Learning to Understand Phrases by Embedding the Dictionary

    Felix Hill;KyungHyun Cho;Anna Korhonen;Yoshua Bengio

  • Statistical metaphor processing

    Ekaterina Shutova;Simone Teufel;Anna Korhonen

  • Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

    David Yarowsky;Timothy Baldwin;Anna Korhonen;Karen Livescu

  • Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing

    Edoardo Maria Ponti;Helen O’Horan;Yevgeni Berzak;Ivan Vulić

  • Zone analysis in biology articles as a basis for information extraction.

    Yoko Mizuta;Anna Korhonen;Tony Mullen;Nigel Collier

  • Extended lexical-semantic classification of English verbs

    Anna Korhonen;Ted Briscoe

  • Intrinsic Evaluation of Word Vectors Fails to Predict Extrinsic Performance

    Billy Chiu;Anna Korhonen;Sampo Pyysalo

  • Improving Verb Clustering with Automatically Acquired Selectional Preferences

    Lin Sun;Anna Korhonen

  • A Large Subcategorization Lexicon for Natural Language Processing Applications.

    Anna Korhonen;Yuval Krymolowski;Ted Briscoe

  • Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrkšić;Ivan Vulić;Diarmuid Ó Séaghdha;Ira Leviant

Frequent Co-Authors

Roi Reichart
Roi Reichart Technion – Israel Institute of Technology
Ivan Vulić
Ivan Vulić University of Cambridge
Felix Hill
Felix Hill Google (United States)
Diana McCarthy
Diana McCarthy University of Cambridge
Nikola Mrksic
Nikola Mrksic PolyAI Limited
Douwe Kiela
Douwe Kiela Stanford University
Martha Palmer
Martha Palmer University of Colorado Boulder
Sampo Pyysalo
Sampo Pyysalo University of Turku
Ted Briscoe
Ted Briscoe Mohamed bin Zayed University of Artificial Intelligence
Nigel Collier
Nigel Collier University of Cambridge

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

Studying computer science in the USA opens doors to a wide range of online degrees and career opportunities. For those seeking budget-friendly advanced education, exploring the most affordable online masters can provide in-depth skills without the heavy financial burden.

Leadership roles in tech, academia, or business may require further study. An accessible option is a doctorate in leadership online or the cheapest online doctorate in educational leadership. These degrees blend management knowledge with your technical background, preparing you for senior or executive positions.

For students just starting out, the easiest associate's degree to get offers a fast track into the tech workforce. This pathway is well-suited for career-changers, or those seeking foundational qualifications before committing to longer programs.

Whether you’re advancing your career or beginning your studies, these online degree pathways offer flexible, affordable options tailored to a wide range of goals within the field of computer science.

Best Scientists Citing Anna Korhonen

Trending Scientists

Recently Published Articles