World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6786
World Ranking
8871
National Ranking
352

Frank Rudzicz 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 Frank Rudzicz 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: 233 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Frank Rudzicz 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 Frank Rudzicz 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

Frank Rudzicz is a researcher affiliated with the University of Toronto in Canada. Their work spans multiple intersecting fields within computer science and medicine, with a focus on the application of artificial intelligence and machine learning to healthcare and cognitive sciences.

The scientist's recent publications cover various topics including digital biomarkers, speech analysis, and medical performance evaluation. Notable recent papers include:

  • "Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations," 2020, Digital Biomarkers
  • "Evaluation of Deep Learning Models for Identifying Surgical Actions and Measuring Performance," 2020, JAMA Network Open
  • "Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech," 2021, Frontiers in Aging Neuroscience
  • "Thinker invariance: enabling deep neural networks for BCI across more people," 2020, Journal of Neural Engineering
  • "A Delphi consensus statement for digital surgery," 2022, npj Digital Medicine

Their main fields of study are:

  • Computer Science
  • Medicine

Within these fields, more specific subfields of study include:

  • Artificial Intelligence
  • Cognitive Neuroscience
  • Epidemiology
  • Computer Vision and Pattern Recognition
  • Physiology

Rudzicz's primary research topics involve:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Machine Learning in Healthcare
  • Speech Recognition and Synthesis
  • Text Readability and Simplification
  • Explainable Artificial Intelligence (XAI)
  • Artificial Intelligence in Healthcare and Education

Frequent coauthors in Rudzicz's work are:

  • Zining Zhu
  • Robert E. Mercer
  • Bai Li
  • Shuja Khalid
  • Jeffrey C. Kwong

The scientist often publishes in venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Pain
  • Journal of Medical Internet Research

Best Publications

  • Linguistic Features Identify Alzheimer's Disease in Narrative Speech.

    Kathleen C. Fraser;Jed A. Meltzer;Frank Rudzicz;Frank Rudzicz

  • The TORGO database of acoustic and articulatory speech from speakers with dysarthria

    Frank Rudzicz;Aravind Kumar Namasivayam;Talya Wolff

  • Artificial Intelligence and the Implementation Challenge.

    James Shaw;James Shaw;Frank Rudzicz;Trevor Jamieson;Trevor Jamieson;Avi Goldfarb

  • A survey of word embeddings for clinical text

    Faiza Khan Khattak;Faiza Khan Khattak;Serena Jeblee;Chloé Pou-Prom;Chloé Pou-Prom;Mohamed Abdalla

  • Detecting Anxiety through Reddit.

    Judy Hanwen Shen;Frank Rudzicz

  • Classifying phonological categories in imagined and articulated speech

    Shunan Zhao;Frank Rudzicz

  • BENDR: Using Transformers and a Contrastive Self-Supervised Learning Task to Learn From Massive Amounts of EEG Data.

    Demetres Kostas;Stéphane Aroca-Ouellette;Frank Rudzicz;Frank Rudzicz

  • Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations.

    Jessica Robin;John E Harrison;Liam D Kaufman;Frank Rudzicz

  • Evaluation of Deep Learning Models for Identifying Surgical Actions and Measuring Performance.

    Shuja Khalid;Mitchell Goldenberg;Teodor Grantcharov;Babak Taati

  • NeuroSpeech: An open-source software for Parkinson's speech analysis

    Juan Rafael Orozco-Arroyave;Juan Camilo Vásquez-Correa;Jesús Francisco Vargas-Bonilla;Raman Arora

  • Articulatory Knowledge in the Recognition of Dysarthric Speech

    F Rudzicz

  • Centroid-based Deep Metric Learning for Speaker Recognition

    Jixuan Wang;Kuan-Chieh Wang;Marc T. Law;Frank Rudzicz

  • Fast incremental LDA feature extraction

    Youness Aliyari Ghassabeh;Frank Rudzicz;Hamid Abrishami Moghaddam

  • To BERT or not to BERT: Comparing Speech and Language-Based Approaches for Alzheimer's Disease Detection.

    Aparna Balagopalan;Benjamin Eyre;Frank Rudzicz;Jekaterina Novikova

  • Adapting acoustic and lexical models to dysarthric speech

    Kinfe Tadesse Mengistu;Frank Rudzicz

  • Speech Interaction with Personal Assistive Robots Supporting Aging at Home for Individuals with Alzheimer’s Disease

    Frank Rudzicz;Rosalie Wang;Momotaz Begum;Alex Mihailidis

  • Adjusting dysarthric speech signals to be more intelligible

    Frank Rudzicz

  • Explainable Artificial Intelligence for Safe Intraoperative Decision Support.

    Lauren Gordon;Lauren Gordon;Teodor Grantcharov;Teodor Grantcharov;Frank Rudzicz;Frank Rudzicz

  • Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech.

    Aparna Balagopalan;Benjamin Eyre;Jessica Robin;Frank Rudzicz

  • Thinker invariance: enabling deep neural networks for BCI across more people.

    Demetres Kostas;Frank Rudzicz;Frank Rudzicz

  • Using linguistic features longitudinally to predict clinical scores for Alzheimer's disease and related dementias

    Maria Yancheva;Kathleen Fraser;Frank Rudzicz

  • Using text and acoustic features to diagnose progressive aphasia and its subtypes.

    Kathleen C. Fraser;Frank Rudzicz;Elizabeth Rochon

Frequent Co-Authors

Graeme Hirst
Graeme Hirst University of Toronto
Gerald Penn
Gerald Penn University of Toronto
Eyal de Lara
Eyal de Lara University of Toronto
Juan Rafael Orozco-Arroyave
Juan Rafael Orozco-Arroyave University of Antioquia
Michael Brudno
Michael Brudno University of Toronto
Elmar Nöth
Elmar Nöth University of Erlangen-Nuremberg
Alex Mihailidis
Alex Mihailidis University of Toronto
Peter M. Clarkson
Peter M. Clarkson University of Queensland
Elizabeth W. Pang
Elizabeth W. Pang Hospital for Sick Children
Elizabeth Rochon
Elizabeth Rochon University of Toronto

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 careers in computer science doesn’t always mean committing to a traditional four-year degree. Today, there are many flexible pathways that can either kickstart your career or help you advance faster. For those seeking quick entry into the tech sector, consider 3-month certificate programs that pay well—these offer practical skills with high earning potential in just a few months.

If you want a foundational college experience but need a shorter time commitment, online associate degree programs provide a solid base in computer science. These programs are often completed in two years or less and can lead straight to entry-level roles or credit transfer to a bachelor’s program.

For professionals looking to upskill, it’s worth exploring the shortest masters degree options in computer science and IT. These accelerated programs allow you to earn a graduate credential in as little as 12 months. Choosing one of the most worthwhile masters degrees can further boost your expertise, promotion prospects, and salary.

Best Scientists Citing Frank Rudzicz

Trending Scientists

Recently Published Articles