World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
10377
World Ranking
4861
National Ranking
291

Ivan Vulić 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 Ivan Vulić 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: 225 publications — 55th percentile

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

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

Ivan Vulić 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 Ivan Vulić 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

Ivan Vulić is affiliated with the University of Cambridge in the United Kingdom. Their research is primarily situated in the field of computer science, with a particular focus on artificial intelligence. Publications also span related subfields such as computer vision and pattern recognition, computer networks and communications, information systems, and molecular biology.

The scientist's work covers various topics including:

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

Recent publications by Ivan Vulić include:

  • Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity, 2020, Computational Linguistics
  • 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
  • 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)
  • On cross-lingual retrieval with multilingual text encoders, 2022, Information Retrieval
  • Wireless Sensor Network in Agriculture: Model of Cyber Security, 2020, Sensors

Ivan Vulić has collaborated frequently with several coauthors, including:

  • Anna Korhonen
  • Goran Glavaš
  • Edoardo Maria Ponti
  • Nigel Collier
  • Jonas Pfeiffer

The most common venues for Ivan Vulić's publications are:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Apollo (University of Cambridge)

Best Publications

  • A Survey Of Cross-lingual Word Embedding Models

    Sebastian Ruder;Ivan Vulić;Anders Søgaard

  • MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer

    Jonas Pfeiffer;Ivan Vulić;Iryna Gurevych;Sebastian Ruder

  • Monolingual and Cross-Lingual Information Retrieval Models Based on (Bilingual) Word Embeddings

    Ivan Vulić;Marie-Francine Moens

  • Hello, It’s GPT-2 - How Can I Help You? Towards the Use of Pretrained Language Models for Task-Oriented Dialogue Systems

    Paweł Budzianowski;Ivan Vulić

  • On the Limitations of Unsupervised Bilingual Dictionary Induction

    Anders Søgaard;Sebastian Ruder;Ivan Vulić

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

    Daniela Gerz;Ivan Vulic;Felix Hill;Roi Reichart

  • From zero to hero: On the limitations of zero-shot language transfer with multilingual transformers

    Anne Lauscher;Vinit Ravishankar;Ivan Vulić;Goran Glavaš

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

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

  • JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages

    Željko Agić;Ivan Vulić

  • How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions

    Goran Glavas;Robert Litschko;Sebastian Ruder;Ivan Vulic

  • Probing Pretrained Language Models for Lexical Semantics

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

  • ConveRT: Efficient and Accurate Conversational Representations from Transformers

    Matthew Henderson;Iñigo Casanueva;Nikola Mrkšić;Pei-Hao Su

  • Bilingual Word Embeddings from Non-Parallel Document-Aligned Data Applied to Bilingual Lexicon Induction

    Ivan Vulić;Marie-Francine Moens

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

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

  • How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models

    Phillip Rust;Jonas Pfeiffer;Ivan Vuli;Sebastian Ruder

  • Skip N-grams and Ranking Functions for Predicting Script Events

    Bram Jans;Steven Bethard;Ivan Vulić;Marie-Francine Moens

  • Probabilistic topic modeling in multilingual settings: An overview of its methodology and applications

    Ivan Vulić;Wim De Smet;Jie Tang;Marie-Francine Moens

  • Identifying Word Translations from Comparable Corpora Using Latent Topic Models

    Ivan Vulić;Wim De Smet;Marie-Francine Moens

  • Bilingual distributed word representations from document-aligned comparable data

    Ivan Vulic;Marie-Francine Moens

  • Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?

    Ivan Vulić;Goran Glavaš;Roi Reichart;Anna Korhonen

  • Unsupervised Cross-Lingual Representation Learning

    Sebastian Ruder;Anders Søgaard;Ivan Vulić

  • 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

Anna Korhonen
Anna Korhonen University of Cambridge
Roi Reichart
Roi Reichart Technion – Israel Institute of Technology
Sebastian Ruder
Sebastian Ruder Google (United States)
Nikola Mrksic
Nikola Mrksic PolyAI Limited
Anders Søgaard
Anders Søgaard University of Copenhagen
Simone Paolo Ponzetto
Simone Paolo Ponzetto University of Mannheim
Diana McCarthy
Diana McCarthy University of Cambridge
Iryna Gurevych
Iryna Gurevych Technical University of Darmstadt
Douwe Kiela
Douwe Kiela Stanford University

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