World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
10508
World Ranking
4136
National Ranking
1954

Douglas W. Oard 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 Douglas W. Oard 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: 373 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Douglas W. Oard 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 Douglas W. Oard 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: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

Douglas W. Oard is affiliated with the University of Maryland, College Park in the United States. Their research principally spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computational Theory and Mathematics, and Human-Computer Interaction.

Their work addresses various topics within their disciplines, notably:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Mathematics, Computing, and Information Processing
  • Information Retrieval and Search Behavior
  • Handwritten Text Recognition Techniques
  • Text and Document Classification Technologies
  • Semantic Web and Ontologies

Douglas W. Oard has contributed to numerous publications, with frequent appearances in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the Association for Information Science and Technology
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • Journal on Computing and Cultural Heritage
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Recent papers include:

  • "C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval" (2022), Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes" (2021), arXiv (Cornell University)
  • "Providing More Efficient Access to Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege" (2022), Journal on Computing and Cultural Heritage
  • "Contextualized Formula Search Using Math Abstract Meaning Representation" (2022), Proceedings of the 31st ACM International Conference on Information & Knowledge Management
  • "Search with Discretion" (2021), Proceedings of the ACM on Human-Computer Interaction

Collaboration forms a significant part of their work, with frequent co-authors including Eugene Yang, Dawn Lawrie, James Mayfield, Richard Zanibbi, and Behrooz Mansouri. These collaborations indicate a network spanning expertise in related computing disciplines.

Best Publications

  • Implicit Feedback for Recommender Systems

    Douglas W Oard;Jinmook Kim

  • A survey of information retrieval and filtering methods

    Christos Faloutsos;Douglas W. Oard

  • Pairwise Document Similarity in Large Collections with MapReduce

    Tamer Elsayed;Jimmy Lin;Douglas Oard

  • Cross-Language Information Retrieval.

    Douglas W. Oard;Anne R. Diekema

  • ENSM-SE at CLEF 2006 : Fuzzy Proximity Method with an Adhoc Influence Function in Evaluation of Multilingual and Multi-modal Information Retrieval 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain

    Carol Peters;Paul Clough;Fredric C. Gey;Jussi Karlgren

  • Confidentiality-preserving rank-ordered search

    Ashwin Swaminathan;Yinian Mao;Guan-Ming Su;Hongmei Gou

  • Advances in Multilingual and Multimodal Information Retrieval

    Carol Peters;Valentin Jijkoun;Thomas Mandl;Henning Müller

  • Textual Data Mining to Support Science and Technology Management

    Paul Losiewicz;Douglas W. Oard;Ronald N. Kostoff

  • A survey of multilingual text retrieval

    Douglas W. Oard;Bonnie J. Dorr

  • The State of the Art in Text Filtering

    Douglas W. Oard

  • Modeling Information Content Using Observable Behavior

    Douglas W Oard;Jinmook Kim

  • A Comparative Study of Query and Document Translation for Cross-Language Information Retrieval

    Douglas W. Oard

  • A Conceptual Framework for Text Filtering Process

    Douglas W. Oard;Gary Marchionini

  • Automatic recognition of spontaneous speech for access to multilingual oral history archives

    W. Byrne;D. Doermann;M. Franz;S. Gustman

  • Dictionary-based techniques for cross-language information retrieval

    Gina-Anne Levow;Douglas W. Oard;Philip Resnik

  • Alternative Approaches for Cross-Language Text Retrieval

    Douglas W. Oard

  • Probabilistic structured query methods

    Kareem Darwish;Douglas W. Oard

  • CLEF Experiments at Maryland: Statistical Stemming and Backoff Translation

    Douglas W. Oard;Gina-Anne Levow;Clara I. Cabezas

  • Serving Users in Many Languages: Cross-Language Information Retrievalfor Digital Libraries

    Douglas W. Oard

  • The Multilingual TEDx Corpus for Speech Recognition and Translation

    Elizabeth Salesky;Matthew Wiesner;Jacob Bremerman;Roldano Cattoni

  • Overview of the CLEF-2006 cross-language speech retrieval track

    Douglas W. Oard;Jianqiang Wang;Gareth J. F. Jones;Ryen W. White

  • Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics

    Mari Ostendorf;Michael Collins;Shri Narayanan;Douglas W. Oard

  • Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

    Tat-Seng Chua;Mun-Kew Leong;Syung Hyon Myaeng;Douglas W. Oard

Frequent Co-Authors

Bonnie J. Dorr
Bonnie J. Dorr University of Florida
Dagobert Soergel
Dagobert Soergel University at Buffalo, State University of New York
Philip Resnik
Philip Resnik University of Maryland, College Park
David Doermann
David Doermann University at Buffalo, State University of New York
Jimmy Lin
Jimmy Lin University of Waterloo
Dina Demner-Fushman
Dina Demner-Fushman National Institutes of Health
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Kareem Darwish
Kareem Darwish Hamad bin Khalifa University
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
Julio Gonzalo
Julio Gonzalo National University of Distance Education

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 Computer Science in the USA opens up numerous academic and career opportunities. Many students consider it among the top 10 best majors for the future due to strong job prospects and high earning potential. However, Computer Science skills also complement other in-demand fields, offering flexibility for career shifts or interdisciplinary roles.

For graduates seeking to expand their expertise, pursuing an easy masters degree might be a practical way to boost qualifications without a heavy workload. Additionally, ambitious professionals interested in teaching or research often look for the most affordable online doctoral programs to minimize costs while advancing their careers.

Those aiming for educational leadership can benefit from accelerated edd programs online that offer fast-track pathways to earn advanced degrees in a shorter time frame. Each of these options helps students and professionals tailor their education to changing industry demands and personal goals.

Best Scientists Citing Douglas W. Oard

Trending Scientists

Recently Published Articles