World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
14721
World Ranking
4731
National Ranking
2202

Mona Diab 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 Mona Diab 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.

Mona Diab 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 Mona Diab 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

Mona Diab is affiliated with Carnegie Mellon University in the United States and has contributed extensively to the field of computer science with a focus on artificial intelligence. Their research spans diverse areas such as natural language processing, topic modeling, and multimodal machine learning applications.

The scientist's publication record includes a significant number of works mainly in computer science, emphasizing artificial intelligence and subfields like computer vision and pattern recognition. Their scholarly output also touches on information systems, sociology and political science, and materials chemistry.

Key research topics associated with Mona Diab include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Hate Speech and Cyberbullying Detection
  • Text Readability and Simplification
  • Multimodal Machine Learning Applications
  • Advanced Text Analysis Techniques
  • Computational Physics and Python Applications

Frequent co-authors collaborating with Mona Diab are:

  • Badr AlKhamissi
  • Xian Li
  • Aslı Çelikyılmaz
  • Naman Goyal
  • Tianlu Wang

The venues where Mona Diab has frequently published include:

  • arXiv (Cornell University)
  • Artificial Intelligence Review
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Journal of Nanoparticle Research
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Selected recent papers authored or co-authored by Mona Diab are:

  • "Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs," 2022, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "Few-shot Learning with Multilingual Language Models," 2021, arXiv (Cornell University)
  • "A Review on Language Models as Knowledge Bases," 2022, arXiv (Cornell University)
  • "Arabic natural language processing for Qur'anic research: a systematic review," 2022, Artificial Intelligence Review
  • "Toxicity assessment of nanoparticles in contact with the skin," 2022, Journal of Nanoparticle Research

Best Publications

  • SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation

    Daniel M. Cer;Mona T. Diab;Eneko Agirre;Iñigo Lopez-Gazpio

  • SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

    Daniel Cer;Mona Diab;Eneko Agirre;Iñigo Lopez-Gazpio

  • SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity

    Eneko Agirre;Daniel Cer;Mona Diab;Aitor Gonzalez-Agirre

  • MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic

    Arfath Pasha;Mohamed Al-Badrashiny;Mona Diab;Ahmed El Kholy

  • SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

    Eneko Agirre;Carmen Banea;Daniel M. Cer;Mona T. Diab

  • SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability

    Eneko Agirre;Carmen Banea;Claire Cardie;Daniel Cer

  • SemEval-2014 Task 10: Multilingual Semantic Textual Similarity

    Eneko Agirre;Carmen Banea;Claire Cardie;Daniel Cer

  • *SEM 2013 shared task: Semantic Textual Similarity

    Eneko Agirre;Daniel Cer;Mona Diab;Aitor Gonzalez-Agirre

  • Automatic tagging of Arabic text: from raw text to base phrase chunks

    Mona Diab;Kadri Hacioglu;Daniel Jurafsky

  • SAMAR: Subjectivity and sentiment analysis for Arabic social media

    Muhammad Abdul-Mageed;Mona Diab;Sandra Kübler

  • FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization

    Esin Durmus;He He;Mona Diab

  • An Unsupervised Method for Word Sense Tagging using Parallel Corpora

    Mona Diab;Philip Resnik

  • Subjectivity and Sentiment Analysis of Modern Standard Arabic

    Muhammad Abdul-Mageed;Mona Diab;Mohammed Korayem

  • Overview for the First Shared Task on Language Identification in Code-Switched Data

    Unknown

  • Overview for the First Shared Task on Language Identification in Code-Switched Data

    Thamar Solorio;Elizabeth Blair;Suraj Maharjan;Steven Bethard

  • AWATIF: A Multi-Genre Corpus for Modern Standard Arabic Subjectivity and Sentiment Analysis

    Muhammad Abdul-Mageed;Mona Diab

  • Arabic Morphological Tagging, Diacritization, and Lemmatization Using Lexeme Models and Feature Ranking

    Ryan Roth;Owen Rambow;Nizar Habash;Mona Diab

  • Conventional Orthography for Dialectal Arabic

    Nizar Habash;Mona Diab;Owen Rambow

  • The Bible as a Parallel Corpus: Annotating the "Book of 2000 Tongues"

    Philip Resnik;Mari Broman Olsen;Mona T. Diab

  • Modeling Sentences in the Latent Space

    Weiwei Guo;Mona Diab

  • Detecting Hallucinated Content in Conditional Neural Sequence Generation

    Chunting Zhou;Graham Neubig;Jiatao Gu;Mona Diab

Frequent Co-Authors

Owen Rambow
Owen Rambow Stony Brook University
Nizar Habash
Nizar Habash New York University Abu Dhabi
Thamar Solorio
Thamar Solorio Mohamed bin Zayed University of Artificial Intelligence
Julia Hirschberg
Julia Hirschberg Columbia University
Eneko Agirre
Eneko Agirre University of the Basque Country
Daniel Cer
Daniel Cer Google (United States)
Kathleen R. McKeown
Kathleen R. McKeown Columbia University
Rada Mihalcea
Rada Mihalcea University of Michigan–Ann Arbor
Janyce Wiebe
Janyce Wiebe University of Pittsburgh
Philip Resnik
Philip Resnik University of Maryland, College Park

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 can offer flexible and affordable pathways for students interested in computer science and related fields. Many learners pursue data science degrees to gain expertise in a rapidly growing and rewarding sector. These programs often blend foundational computer science with high-demand analytical skills that employers seek.

For those considering engineering careers, understanding electrical engineering online tuition costs can help you compare options and find programs that fit your budget. Online courses typically reduce additional expenses, making high-quality degrees more accessible than traditional on-campus routes.

If you’re looking for fast entry into the workforce, obtaining certifications that pay well can be a smart investment. Many tech-related certifications can be completed quickly and lead to lucrative careers, especially in IT and cybersecurity.

Ambitious students may also be interested in the quickest cheapest masters degree programs. These allow graduates to boost career prospects in less time and at a lower cost, making advanced education more attainable for working professionals.

Best Scientists Citing Mona Diab

Trending Scientists