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D-Index & Metrics

Computer Science

D-Index
67
Citations
23469
World Ranking
2158
National Ranking
1084

Dana S. Nau 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 Dana S. Nau 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: 367 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.

Dana S. Nau 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 Dana S. Nau 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: 67 D-Index — 85th percentile

85% 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

  • 2013 - ACM Fellow For contributions to automated search and planning.
  • 1996 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For contributions to the fields of AI search algorithms, AI planning, and AI applications in design and manufacturing.

Overview

Dana S. Nau is affiliated with the University of Maryland, College Park in the United States. Their research primarily focuses on computer science with an emphasis on artificial intelligence and related subfields.

The main fields of study for Dana S. Nau include:

  • Computer Science

The subfields of study where Nau has significant contributions are:

  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Sociology and Political Science
  • Public Health, Environmental and Occupational Health

Key topics covered in their work include:

  • AI-based Problem Solving and Planning
  • Evolutionary Game Theory and Cooperation
  • Service-Oriented Architecture and Web Services
  • Logic, Reasoning, and Knowledge
  • Reinforcement Learning in Robotics
  • Cultural Differences and Values
  • Semantic Web and Ontologies

Their publication record includes papers in various venues. Frequent publication venues are:

  • arXiv (Cornell University)
  • Proceedings of the International Conference on Automated Planning and Scheduling
  • Proceedings of the International Florida Artificial Intelligence Research Society Conference
  • The Lancet Planetary Health
  • American Psychologist

Recent papers authored or co-authored by Dana S. Nau include:

  • The relationship between cultural tightness-looseness and COVID-19 cases and deaths: a global analysis (2021), The Lancet Planetary Health
  • HTN Problem Spaces: Structure, Algorithms, Termination (2021), Proceedings of the International Symposium on Combinatorial Search
  • Deliberative acting, planning and learning with hierarchical operational models (2021), Artificial Intelligence
  • Integrating Acting, Planning, and Learning in Hierarchical Operational Models (2020), Proceedings of the International Conference on Automated Planning and Scheduling
  • Integrating evolutionary game theory and cross-cultural psychology to understand cultural dynamics (2021), American Psychologist

Frequent co-authors who have collaborated with Dana S. Nau include:

  • Sunandita Patra
  • Malik Ghallab
  • Paolo Traverso
  • Michele J. Gelfand
  • Xinyue Pan

Dana S. Nau has also contributed to book publications. One known book is:

  • Acting, Planning, and Learning, to be published by Cambridge University Press in 2025

Among distinctions recognizing their professional contributions are:

  • ACM Fellow (2013) for contributions to automated search and planning
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) (1996) for contributions to AI search algorithms, AI planning, and AI applications in design and manufacturing

Best Publications

  • Automated Planning, Theory And Practice

    Malik Ghallab;Dana S. Nau;Paolo Traverso

  • SHOP2: an HTN planning system

    Dana Nau;Tsz-Chiu Au;Okhtay Ilghami;Ugur Kuter

  • Automated Planning: Theory & Practice

    Dana Nau;Malik Ghallab;Paolo Traverso

  • HTN planning for Web Service composition using SHOP2

    Evren Sirin;Bijan Parsia;Dan Wu;James Hendler

  • HTN planning: complexity and expressivity

    Kutluhan Erol;James Hendler;Dana S. Nau

  • SHOP: Simple Hierarchical Ordered Planner

    Dana S. Nau;Yue Cao;Amnon Lotem;Hector Muñoz-Avila

  • Automating DAML-S web services composition using SHOP2

    Dan Wu;Bijan Parsia;Evren Sirin;James Hendler

  • UMCP: a sound and complete procedure for hierarchical task-network planning

    Kutluhan Erol;James Hendler;Dana S. Nau

  • Diagnostic Expert Systems Based on a Set Covering Model

    James A. Reggia;Dana S. Nau;Pearl Y. Wang

  • Automated Planning and Acting

    Malik Ghallab;Dana Nau;Paolo Traverso

  • Complexity, decidability and undecidability results for domain-independent planning

    Kutluhan Erol;Dana S. Nau;V. S. Subrahmanian

  • On the complexity of blocks-world planning

    Naresh Gupta;Dana S. Nau

  • Semantics for hierarchical task-network planning

    Kutluhan Erol;James Hendler;Dana S. Nau

  • Complexity results for HTN planning

    Kutluhan Erol;James Handler;Dana S. Nau

  • Expert Computer Systems

    D. S. Nau

  • Systematic approach to analysing the manufacturability of machined parts

    Satyandra K Gupta;Dana S Nau

  • Automatic Web Services Composition Using SHOP2

    Dan Wu;Evren Sirin;James A Hendler;Dana S Nau

  • A formal model of diagnostic inference. I. Problem formulation and decomposition

    James A. Reggia;Dana S. Nau;Pearl Y. Wang

  • Societal threat and cultural variation in the strength of social norms: An evolutionary basis

    Patrick Roos;Michele Gelfand;Dana Nau;Janetta Lun

  • Automated manufacturability analysis: a survey

    Satyandra K. Gupta;Diganta Das;William C. Regli;Dana S. Nau

Frequent Co-Authors

Satyandra K. Gupta
Satyandra K. Gupta University of Southern California
Paolo Traverso
Paolo Traverso Fondazione Bruno Kessler
James A. Hendler
James A. Hendler Rensselaer Polytechnic Institute
Héctor Muñoz-Avila
Héctor Muñoz-Avila Lehigh University
William C. Regli
William C. Regli University of Maryland, College Park
V. S. Subrahmanian
V. S. Subrahmanian Dartmouth College
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
James A. Reggia
James A. Reggia University of Maryland, College Park
David W. Aha
David W. Aha United States Naval Research Laboratory
Michele J. Gelfand
Michele J. Gelfand Stanford University

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