World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8149
World Ranking
7571
National Ranking
3286

Andrea L. Thomaz 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 Andrea L. Thomaz 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: 171 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Andrea L. Thomaz 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 Andrea L. Thomaz 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Andrea L. Thomaz is affiliated with The University of Texas at Austin in the United States. Their research primarily intersects the fields of Computer Science and Engineering with a significant focus on Artificial Intelligence and Control and Systems Engineering. Additional subfields include Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, and Aerospace Engineering.

The main topics of Andrea L. Thomaz's research work cover:

  • Robot Manipulation and Learning
  • Reinforcement Learning in Robotics
  • Model Reduction and Neural Networks
  • AI-based Problem Solving and Planning
  • Speech and dialogue systems
  • Robotics and Sensor-Based Localization
  • Modular Robots and Swarm Intelligence

Their recent publications highlight diverse aspects of robotics, machine learning, and AI-driven system identification. Notable papers include:

  • "Iterative residual tuning for system identification and sim-to-real robot learning," 2020, Autonomous Robots
  • "Modeling and Learning Constraints for Creative Tool Use," 2021, Frontiers in Robotics and AI
  • "Abstraction in data-sparse task transfer," 2021, Artificial Intelligence
  • "Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots," 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • "Multiparameter Real-World System Identification Using Iterative Residual Tuning," 2021, Journal of Mechanisms and Robotics

Andrea L. Thomaz has frequently collaborated with several researchers across these publications. Frequent coauthors include Tesca Fitzgerald, Ashok K. Goel, Adam Allevato, Mitch Pryor, and Akanksha Saran.

Their work has been published in various venues such as:

  • arXiv (Cornell University)
  • Autonomous Robots
  • Frontiers in Robotics and AI
  • Artificial Intelligence
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Best Publications

  • Effects of nonverbal communication on efficiency and robustness in human-robot teamwork

    C. Breazeal;C.D. Kidd;A.L. Thomaz;G. Hoffman

  • Teachable robots: Understanding human teaching behavior to build more effective robot learners

    Andrea L. Thomaz;Cynthia Breazeal

  • Policy Shaping: Integrating Human Feedback with Reinforcement Learning

    Shane Griffith;Kaushik Subramanian;Jonathan Scholz;Charles Isbell

  • Reinforcement learning with human teachers: evidence of feedback and guidance with implications for learning performance

    Andrea L. Thomaz;Cynthia Breazeal

  • Trajectories and keyframes for kinesthetic teaching: a human-robot interaction perspective

    Baris Akgun;Maya Cakmak;Jae Wook Yoo;Andrea Lockerd Thomaz

  • Robot Learning from Human Teachers

    Sonia Chernova;Andrea L. Thomaz

  • Designing robot learners that ask good questions

    Maya Cakmak;Andrea L. Thomaz

  • Cheese: tracking mouse movement activity on websites, a tool for user modeling

    Florian Mueller;Andrea Lockerd

  • Keyframe-based Learning from Demonstration Method and Evaluation

    Baris Akgun;Maya Cakmak;Karl Jiang;Andrea Lockerd Thomaz

  • Designing Interactions for Robot Active Learners

    Maya Cakmak;Crystal Chao;Andrea L Thomaz

  • Tutelage and socially guided robot learning

    A. Lockerd;C. Breazeal

  • TUTELAGE AND COLLABORATION FOR HUMANOID ROBOTS

    Cynthia Breazeal;Andrew G. Brooks;Jesse Gray;Guy Hoffman

  • Teaching and Working with Robots as a Collaboration

    Cynthia Breazeal;Guy Hoffman;Andrea Lockerd

  • Using perspective taking to learn from ambiguous demonstrations

    Cynthia Breazeal;Matt Berlin;Andrew G. Brooks;Jesse Gray

  • Reinforcement Learning with Human Teachers: Understanding How People Want to Teach Robots

    A.L. Thomaz;G. Hoffman;C. Breazeal

  • Computational Human-Robot Interaction

    Andrea Thomaz;Guy Hoffman;Maya Cakmak

  • Transparent active learning for robots

    Crystal Chao;Maya Cakmak;Andrea L. Thomaz

  • Interactive Task Learning

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

  • An Investigation of Responses to Robot-Initiated Touch in a Nursing Context

    Tiffany L. Chen;Chih-Hung Aaron King;Andrea Lockerd Thomaz;Charles C. Kemp

  • Touched by a robot: an investigation of subjective responses to robot-initiated touch

    Tiffany L. Chen;Chih-Hung King;Andrea L. Thomaz;Charles C. Kemp

  • Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction

    Gerhard Sagerer;Michita Imai;Tony Belpaeme;Andrea Thomaz

Frequent Co-Authors

Maya Cakmak
Maya Cakmak University of Washington
Sonia Chernova
Sonia Chernova Georgia Institute of Technology
Ashok K. Goel
Ashok K. Goel Georgia Institute of Technology
Guy Hoffman
Guy Hoffman Cornell University
C. Karen Liu
C. Karen Liu Stanford University
Aaron F. Bobick
Aaron F. Bobick Washington University in St. Louis
Bilge Mutlu
Bilge Mutlu University of Wisconsin–Madison
Gerhard Sagerer
Gerhard Sagerer Bielefeld University
Aaron D. Ames
Aaron D. Ames California Institute of Technology

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

Expanding your knowledge in Computer Science doesn’t always mean spending years on campus. Today, students can access quick masters degrees online, streamlining the journey to an advanced credential. These accelerated programs allow working professionals and career changers to fast-track their education, often completing a master’s in as little as a year.

For those seeking the best return on investment, reviewing the most in demand masters degrees is critical. Computer Science consistently ranks among top fields for earning potential and job growth, making graduate study an attractive option.

Not ready for a full bachelor’s or master’s program? Numerous associates degrees online are available, providing a strong technical foundation for immediate entry into IT roles or for transfer to a four-year university.

Cost is an important factor for many students. The rise of affordable online courses means you can access quality education without taking on excessive debt, making your journey into Computer Science flexible and financially accessible.

Best Scientists Citing Andrea L. Thomaz

Trending Scientists

Recently Published Articles