World's Best Scientists 2026 revealed!
Matthias Scheutz

Matthias Scheutz

D-Index & Metrics

Computer Science

D-Index
59
Citations
10137
World Ranking
3497
National Ranking
1683

Matthias Scheutz 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 Matthias Scheutz 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: 353 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Matthias Scheutz 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 Matthias Scheutz 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Overview

Matthias Scheutz is affiliated with Tufts University in the United States and has a significant body of research primarily within the field of Computer Science. Their work spans several subfields including Artificial Intelligence, Social Psychology, Cognitive Neuroscience, Control and Systems Engineering, and Computer Vision and Pattern Recognition.

The research of Matthias Scheutz covers a range of topics, with a particular focus on:

  • Social Robot Interaction and Human-Robot Interaction (HRI)
  • Reinforcement Learning in Robotics
  • Ethics and Social Impacts of Artificial Intelligence
  • AI-based Problem Solving and Planning
  • Speech and dialogue systems
  • Robot Manipulation and Learning
  • Domain Adaptation and Few-Shot Learning

Their recent publications include:

  • "Spoken language interaction with robots: Recommendations for future research" (2021) published in Computer Speech & Language
  • "The Interplay Between Emotional Intelligence, Trust, and Gender in Human-Robot Interaction" (2020) published in International Journal of Social Robotics
  • "A Touching Connection: How Observing Robotic Touch Can Affect Human Trust in a Robot" (2021) published in International Journal of Social Robotics
  • "Cognitive cascades: How to model (and potentially counter) the spread of fake news" (2022) published in PLoS ONE
  • "An Attachment Framework for Human-Robot Interaction" (2021) published in International Journal of Social Robotics

Frequent co-authors collaborating with Matthias Scheutz are Theresa Law, Shuchin Aeron, Meia Chita-Tegmark, Boyang Lyu, and Prakash Ishwar.

Their work has been disseminated through various publication venues, with the most frequent being:

  • arXiv (Cornell University)
  • ACM Transactions on Human-Robot Interaction
  • International Journal of Social Robotics
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Access

Best Publications

  • Development environments for autonomous mobile robots: A survey

    James Kramer;Matthias Scheutz

  • Mapping the Landscape of Human-Level Artificial General Intelligence

    Sam S. Adams;Itamar Arel;Joscha Bach;Robert Coop

  • Robot social presence and gender: do females view robots differently than males?

    Paul Schermerhorn;Matthias Scheutz;Charles R. Crowell

  • What to do and how to do it: Translating natural language directives into temporal and dynamic logic representation for goal management and action execution

    Juraj Dzifcak;Matthias Scheutz;Chitta Baral;Paul Schermerhorn

  • First steps toward natural human-like HRI

    Matthias Scheutz;Paul Schermerhorn;James Kramer;David Anderson

  • The Architectural Basis of Affective States and Processes

    Aaron Sloman;Ron Chrisley;Matthias Scheutz

  • Assistive Robots for the Social Management of Health: A Framework for Robot Design and Human-Robot Interaction Research.

    Meia Chita-Tegmark;Matthias Scheutz

  • The utility of affect expression in natural language interactions in joint human-robot tasks

    Matthias Scheutz;Paul Schermerhorn;James Kramer

  • What we can and cannot (yet) do with functional near infrared spectroscopy

    Megan K. Strait;Matthias Scheutz

  • Brainput: enhancing interactive systems with streaming fnirs brain input

    Erin Solovey;Paul Schermerhorn;Matthias Scheutz;Angelo Sassaroli

  • Interactive Task Learning

    John E. Laird;Kevin Gluck;John Anderson;Kenneth D. Forbus

  • Planning for human-robot teaming in open worlds

    Kartik Talamadupula;J. Benton;Subbarao Kambhampati;Paul Schermerhorn

  • When Physical Systems Realize Functions...

    Matthias Scheutz

  • Computationalism: New Directions

    Matthias Scheutz

  • Let me tell you! investigating the effects of robot communication strategies in advice-giving situations based on robot appearance, interaction modality and distance

    Megan Strait;Cody Canning;Matthias Scheutz

  • Incremental natural language processing for HRI

    Timothy Brick;Matthias Scheutz

  • Tell me when and why to do it!: run-time planner model updates via natural language instruction

    Rehj Cantrell;J. Benton;Kartik Talamadupula;Subbarao Kambhampati

  • Useful roles of emotions in artificial agents: a case study from artificial life

    Matthias Scheutz

  • How Robots Can Affect Human Behavior: Investigating the Effects of Robotic Displays of Protest and Distress

    Gordon Briggs;Matthias Scheutz

  • The “big red button” is too late: an alternative model for the ethical evaluation of AI systems

    Thomas Arnold;Matthias Scheutz

  • Moral competence in social robots

    Bertram F. Malle;Matthias Scheutz

  • Value Alignment or Misalignment – What Will Keep Systems Accountable?

    Thomas Arnold;Daniel Kasenberg;Matthias Scheutz

Frequent Co-Authors

Bertram F. Malle
Bertram F. Malle Brown University
Subbarao Kambhampati
Subbarao Kambhampati Arizona State University
Aaron Sloman
Aaron Sloman University of Birmingham
Michael Beetz
Michael Beetz University of Bremen
Michael Levin
Michael Levin Tufts University
Bennett I. Bertenthal
Bennett I. Bertenthal Indiana University
Yiannis Demiris
Yiannis Demiris Imperial College London
Chen Yu
Chen Yu The University of Texas at Austin
Kerstin Dautenhahn
Kerstin Dautenhahn University of Waterloo
Ronald C. Arkin
Ronald C. Arkin Georgia Institute of Technology

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