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D-Index & Metrics

Computer Science

D-Index
33
Citations
23959
World Ranking
12335
National Ranking
4991

Yuval Tassa 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 Yuval Tassa 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: 54 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

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

Yuval Tassa 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 Yuval Tassa 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Yuval Tassa is a researcher affiliated with Google in the United States. Their primary fields of study include computer science and engineering, with a significant focus on artificial intelligence, control and systems engineering, and biomedical engineering. The subfields of their work also encompass computer vision and pattern recognition, as well as aerospace engineering.

The main topics addressed in their research cover reinforcement learning in robotics, robot manipulation and learning, robotic locomotion and control, muscle activation and electromyography studies, human pose and action recognition, biomimetic flight and propulsion mechanisms, and insect behavior and control techniques.

Yuval Tassa has contributed to numerous publications, with notable recent papers including:

  • "dm_control: Software and tasks for continuous control," 2020, Software Impacts
  • "Learning agile soccer skills for a bipedal robot with deep reinforcement learning," 2024, Science Robotics
  • "Catch & Carry," 2020, ACM Transactions on Graphics
  • "From motor control to team play in simulated humanoid football," 2022, Science Robotics
  • "A virtual rodent predicts the structure of neural activity across behaviours," 2024, Nature

The venues in which Yuval Tassa frequently publishes include arXiv (Cornell University), Nature, Science Robotics, Zenodo (CERN European Organization for Nuclear Research), and Software Impacts.

Collaborations form an important aspect of their research activities. Frequent co-authors include Josh Merel, Leonard Hasenclever, Nicolas Heess, Saran Tunyasuvunakool, and Tuomas Haarnoja.

Best Publications

  • Continuous control with deep reinforcement learning

    Timothy P. Lillicrap;Jonathan J. Hunt;Alexander Pritzel;Nicolas Heess

  • MuJoCo: A physics engine for model-based control

    Emanuel Todorov;Tom Erez;Yuval Tassa

  • Emergence of Locomotion Behaviours in Rich Environments

    Nicolas Heess;Dhruva Tb;Srinivasan Sriram;Jay Lemmon

  • Synthesis and stabilization of complex behaviors through online trajectory optimization

    Yuval Tassa;Tom Erez;Emanuel Todorov

  • DeepMind Control Suite

    Yuval Tassa;Yotam Doron;Alistair Muldal;Tom Erez

  • Control-limited differential dynamic programming

    Yuval Tassa;Nicolas Mansard;Emo Todorov

  • Learning continuous control policies by stochastic value gradients

    Nicolas Heess;Greg Wayne;David Silver;Timothy Lillicrap

  • Attend, infer, repeat: fast scene understanding with generative models

    S. M. Ali Eslami;Nicolas Heess;Theophane Weber;Yuval Tassa

  • Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX

    Tom Erez;Yuval Tassa;Emanuel Todorov

  • Safe Exploration in Continuous Action Spaces

    Gal Dalal;Krishnamurthy Dvijotham;Matej Vecerik;Todd Hester

  • Maximum a Posteriori Policy Optimisation

    Abbas Abdolmaleki;Jost Tobias Springenberg;Yuval Tassa;Rémi Munos

  • Whole-body model-predictive control applied to the HRP-2 humanoid

    J. Koenemann;A. Del Prete;Y. Tassa;E. Todorov

  • Learning human behaviors from motion capture by adversarial imitation

    Josh Merel;Yuval Tassa;Dhruva Tb;Sriram Srinivasan

  • Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

    Ivaylo Popov;Nicolas Heess;Timothy P. Lillicrap;Roland Hafner

  • Learning and Transfer of Modulated Locomotor Controllers

    Nicolas Heess;Gregory Wayne;Yuval Tassa;Timothy P. Lillicrap

  • An integrated system for real-time model predictive control of humanoid robots

    Tom Erez;Kendall Lowrey;Yuval Tassa;Vikash Kumar

  • dm_control: Software and Tasks for Continuous Control

    Yuval Tassa;Saran Tunyasuvunakool;Alistair Muldal;Yotam Doron

  • Receding Horizon Differential Dynamic Programming

    Yuval Tassa;Tom Erez;William D. Smart

  • Stochastic Differential Dynamic Programming

    Evangelos Theodorou;Yuval Tassa;Emo Todorov

  • Catch & Carry: reusable neural controllers for vision-guided whole-body tasks

    Josh Merel;Saran Tunyasuvunakool;Arun Ahuja;Yuval Tassa

  • Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts

    Tom Erez;Yuval Tassa;Emanuel Todorov

Frequent Co-Authors

Nicolas Heess
Nicolas Heess DeepMind (United Kingdom)
Emanuel Todorov
Emanuel Todorov University of Washington
Timothy P. Lillicrap
Timothy P. Lillicrap University College London
David Silver
David Silver DeepMind (United Kingdom)
Martin Riedmiller
Martin Riedmiller DeepMind (United Kingdom)
Jost Tobias Springenberg
Jost Tobias Springenberg University of Freiburg
Vikash Kumar
Vikash Kumar University of Washington
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA
Nicolas Mansard
Nicolas Mansard Laboratory for Analysis and Architecture of Systems
Javier R. Movellan
Javier R. Movellan University of California, San Diego

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