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Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
153
Citations
97923
World Ranking
33
National Ranking
19

Sergey Levine 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 Sergey Levine 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 552 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Sergey Levine 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 Sergey Levine sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 153 D-Index — 100th percentile

100% 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

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2019 - Fellow of Alfred P. Sloan Foundation

Overview

Sergey Levine is affiliated with the University of California, Berkeley in the United States. Their primary field of study is Computer Science, with a significant focus on Artificial Intelligence. They have published extensively in this domain, contributing 595 publications overall, including subfields such as Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering, and Management Science and Operations Research.

Their research topics encompass a variety of areas within machine learning and robotics. Key topics include Reinforcement Learning in Robotics, Domain Adaptation and Few-Shot Learning, Robot Manipulation and Learning, Multimodal Machine Learning Applications, Adversarial Robustness in Machine Learning, Machine Learning and Data Classification, and Machine Learning and Algorithms.

Frequent coauthors working with Sergey Levine include:

  • Chelsea Finn
  • Aviral Kumar
  • Benjamin Eysenbach
  • Karol Hausman
  • Pieter Abbeel

Common publication venues for Sergey Levine are as follows:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 International Conference on Robotics and Automation (ICRA)
  • The International Journal of Robotics Research
  • ACM Transactions on Graphics

The following recent papers represent a selection of Sergey Levine's work, indicating their ongoing interests and contributions:

  • Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems, 2020, arXiv (Cornell University)
  • Conservative Q-Learning for Offline Reinforcement Learning, 2020, arXiv (Cornell University)
  • Do As I Can, Not As I Say: Grounding Language in Robotic Affordances, 2022, arXiv (Cornell University)
  • How to train your robot with deep reinforcement learning: lessons we have learned, 2021, The International Journal of Robotics Research
  • PaLM-E: An Embodied Multimodal Language Model, 2023, arXiv (Cornell University)

Among recognitions, Sergey Levine received the Fellow of Alfred P. Sloan Foundation award in 2019.

Best Publications

  • Model-agnostic meta-learning for fast adaptation of deep networks

    Chelsea Finn;Pieter Abbeel;Sergey Levine

  • Trust Region Policy Optimization

    John Schulman;Sergey Levine;Pieter Abbeel;Michael Jordan

  • Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

    Tuomas Haarnoja;Aurick Zhou;Pieter Abbeel;Sergey Levine

  • End-to-end training of deep visuomotor policies

    Sergey Levine;Chelsea Finn;Trevor Darrell;Pieter Abbeel

  • Trust Region Policy Optimization

    John Schulman;Sergey Levine;Philipp Moritz;Michael I. Jordan

  • High-Dimensional Continuous Control Using Generalized Advantage Estimation

    John Schulman;Philipp Moritz;Sergey Levine;Michael Jordan

  • Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection

    Sergey Levine;Peter Pastor;Alex Krizhevsky;Julian Ibarz

  • Soft Actor-Critic Algorithms and Applications

    Tuomas Haarnoja;Aurick Zhou;Kristian Hartikainen;George Tucker

  • Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates

    Shixiang Gu;Ethan Holly;Timothy Lillicrap;Sergey Levine

  • QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

    Dmitry Kalashnikov;Alex Irpan;Peter Pastor;Julian Ibarz

  • Recurrent Network Models for Human Dynamics

    Katerina Fragkiadaki;Sergey Levine;Panna Felsen;Jitendra Malik

  • Guided Policy Search

    Sergey Levine;Vladlen Koltun

  • Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

    Sergey Levine;Aviral Kumar;George Tucker;Justin Fu

  • Unsupervised Learning for Physical Interaction through Video Prediction

    Chelsea Finn;Ian J. Goodfellow;Sergey Levine

  • Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

    Anusha Nagabandi;Gregory Kahn;Ronald S. Fearing;Sergey Levine

  • Reinforcement learning with deep energy-based policies

    Tuomas Haarnoja;Haoran Tang;Pieter Abbeel;Sergey Levine

  • Continuous deep Q-learning with model-based acceleration

    Shixiang Gu;Timothy Lillicrap;Ilya Sutskever;Sergey Levine

  • DeepMimic: example-guided deep reinforcement learning of physics-based character skills

    Xue Bin Peng;Pieter Abbeel;Sergey Levine;Michiel van de Panne

  • PaLM-E: An Embodied Multimodal Language Model

    Unknown

  • Guided cost learning: deep inverse optimal control via policy optimization

    Chelsea Finn;Sergey Levine;Pieter Abbeel

  • Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

    Aravind Rajeswaran;Vikash Kumar;Abhishek Gupta;Giulia Vezzani

  • Conservative Q-Learning for Offline Reinforcement Learning

    Aviral Kumar;Aurick Zhou;George Tucker;Sergey Levine

  • Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

    Kurtland Chua;Roberto Calandra;Rowan McAllister;Sergey Levine

  • D4RL: Datasets for Deep Data-Driven Reinforcement Learning

    Justin Fu;Aviral Kumar;Ofir Nachum;George Tucker

  • Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection

    Sergey Levine;Peter Pastor;Alex Krizhevsky;Deirdre Quillen

  • Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

    Tianhe Yu;Deirdre Quillen;Zhanpeng He;Ryan Julian

Frequent Co-Authors

Pieter Abbeel
Pieter Abbeel University of California, Berkeley
Chelsea Finn
Chelsea Finn Stanford University
Shixiang Gu
Shixiang Gu Google (United States)
Vikash Kumar
Vikash Kumar University of Washington
Trevor Darrell
Trevor Darrell University of California, Berkeley
Jitendra Malik
Jitendra Malik University of California, Berkeley
George Tucker
George Tucker Google (United States)
Yoshua Bengio
Yoshua Bengio University of Montreal
Anca D. Dragan
Anca D. Dragan University of California, Berkeley
Timothy P. Lillicrap
Timothy P. Lillicrap University College London

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