World's Best Scientists 2026 revealed!
Isabelle Augenstein

Isabelle Augenstein

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
40
Citations
6217
World Ranking
660
National Ranking
2

Computer Science

D-Index
34
Citations
5114
World Ranking
12154
National Ranking
59

Isabelle Augenstein 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 Isabelle Augenstein 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: 241 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.

Isabelle Augenstein 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 Isabelle Augenstein 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Isabelle Augenstein is affiliated with the University of Copenhagen in Denmark. Their research primarily spans the field of Computer Science, with a focus on subfields such as Artificial Intelligence, Sociology and Political Science, Information Systems, Gender Studies, and Computer Vision and Pattern Recognition.

The scientist's work covers a range of topics, including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Hate Speech and Cyberbullying Detection
  • Misinformation and Its Impacts
  • Explainable Artificial Intelligence (XAI)
  • Sentiment Analysis and Opinion Mining
  • Ethics and Social Impacts of AI

Isabelle Augenstein has contributed to numerous scholarly venues, frequently publishing in:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Computing Surveys
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • PLoS ONE

Their recent papers highlight diverse research interests and include:

  • Factuality challenges in the era of large language models and opportunities for fact-checking, 2024, Nature Machine Intelligence
  • Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence, 2021, Information Fusion
  • A Survey on Stance Detection for Mis- and Disinformation Identification, 2022, Findings of the Association for Computational Linguistics: NAACL 2022
  • A Survey on Gender Bias in Natural Language Processing, 2021, arXiv (Cornell University)
  • Detecting Harmful Content on Online Platforms: What Platforms Need vs. Where Research Efforts Go, 2023, ACM Computing Surveys

Frequent collaborators with whom Augenstein has co-authored multiple publications include:

  • Arnav Arora
  • Pepa Atanasova
  • Preslav Nakov
  • Christina Lioma
  • Karolina Stańczak

Best Publications

  • Stance detection with bidirectional conditional encoding

    Isabelle Augenstein;Tim Rocktäschel;Andreas Vlachos;Kalina Bontcheva

  • SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications

    Isabelle Augenstein;Mrinal Das;Sebastian Riedel;Lakshmi Vikraman

  • emoji2vec: Learning Emoji Representations from their Description

    Ben Eisner;Tim Rocktäschel;Isabelle Augenstein;Matko Bosnjak

  • Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

    Unknown

  • Latent Multi-Task Architecture Learning

    Sebastian Ruder;Joachim Bingel;Isabelle Augenstein;Anders Søgaard

  • A simple but tough-to-beat baseline for the Fake News Challenge stance detection task

    Benjamin Riedel;Isabelle Augenstein;Georgios P. Spithourakis;Sebastian Riedel

  • MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims

    Isabelle Augenstein;Christina Lioma;Dongsheng Wang;Lucas Chaves Lima

  • Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

    Andreas Holzinger;Andreas Holzinger;Matthias Dehmer;Frank Emmert-Streib;Rita Cucchiara

  • A Diagnostic Study of Explainability Techniques for Text Classification.

    Pepa Atanasova;Jakob Grue Simonsen;Christina Lioma;Isabelle Augenstein

  • Sluice networks: Learning what to share between loosely related tasks.

    Sebastian Ruder;Joachim Bingel;Isabelle Augenstein;Anders Søgaard

  • Discourse-aware rumour stance classification in social media using sequential classifiers

    Arkaitz Zubiaga;Elena Kochkina;Elena Kochkina;Maria Liakata;Maria Liakata;Rob Procter;Rob Procter

  • Learning what to share between loosely related tasks

    Sebastian Ruder;Joachim Bingel;Isabelle Augenstein;Anders Søgaard

  • Generating Fact Checking Explanations

    Pepa Atanasova;Jakob Grue Simonsen;Christina Lioma;Isabelle Augenstein

  • LODifier: generating linked data from unstructured text

    Isabelle Augenstein;Sebastian Padó;Sebastian Rudolph

  • Generalisation in named entity recognition

    Isabelle Augenstein;Leon Derczynski;Kalina Bontcheva

  • Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM

    Elena Kochkina;Maria Liakata;Isabelle Augenstein

  • A Survey on Stance Detection for Mis- and Disinformation Identification

    Momchil Hardalov;Arnav Arora;Preslav Nakov;Isabelle Augenstein

  • Zero-Shot Cross-Lingual Transfer with Meta Learning

    Farhad Nooralahzadeh;Giannis Bekoulis;Johannes Bjerva;Isabelle Augenstein

  • A Supervised Approach to Extractive Summarisation of Scientific Papers

    Ed Collins;Isabelle Augenstein;Sebastian Riedel

  • Factuality challenges in the era of large language models and opportunities for fact-checking

    Unknown

  • Multi-Task Learning of Pairwise Sequence Classification Tasks over Disparate Label Spaces

    Isabelle Augenstein;Sebastian Ruder;Anders Søgaard

  • Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings

    Unknown

  • emoji2vec: Learning Emoji Representations from their Description

    Ben Eisner;Tim Rocktäschel;Isabelle Augenstein;Matko Bošnjak

  • Multi-Task Learning of Keyphrase Boundary Classification

    Isabelle Augenstein;Anders Søgaard

  • Generalisation in Named Entity Recognition: A Quantitative Analysis

    Isabelle Augenstein;Leon Derczynski;Kalina Bontcheva

Frequent Co-Authors

Anders Søgaard
Anders Søgaard University of Copenhagen
Ryan Cotterell
Ryan Cotterell ETH Zurich
Sebastian Riedel
Sebastian Riedel University College London
Kalina Bontcheva
Kalina Bontcheva University of Sheffield
Fabio Ciravegna
Fabio Ciravegna University of Turin
Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Tim Rocktäschel
Tim Rocktäschel University College London
Sebastian Ruder
Sebastian Ruder Google (United States)
Maria Liakata
Maria Liakata Queen Mary University of London
Hanna Wallach
Hanna Wallach Microsoft (United States)

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

If you’re exploring Computer Science studies in the USA, there are several online degree options that can support your career growth. Many students begin with an associate’s degree for a flexible, affordable start. For those looking to balance work and study, you might find the easiest associate's degree to get and start building basic technical skills.

Looking to advance your expertise? Consider an affordable master degree online. These programs offer specialized knowledge in areas like software engineering or data analytics at a lower cost, making postgraduate education more accessible.

For those drawn to leadership roles in technology or academia, pursuing an affordable doctoral programs in leadership can strengthen your credentials and open doors to executive or educational positions.

Several reputable universities, such as the university of north georgia, offer flexible and affordable online pathways—making it easier than ever to study while you work. Exploring these online degrees can empower your next steps in the evolving tech landscape.

Best Scientists Citing Isabelle Augenstein

Trending Scientists

Recently Published Articles