World's Best Scientists 2026 revealed!
Wojciech Marian Czarnecki

Wojciech Marian Czarnecki

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
34
Citations
12950
World Ranking
863
National Ranking
141

Computer Science

D-Index
34
Citations
10305
World Ranking
11897
National Ranking
4851

Wojciech Marian Czarnecki 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 Wojciech Marian Czarnecki 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: 90 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Wojciech Marian Czarnecki 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 Wojciech Marian Czarnecki 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: 34 D-Index — 16th percentile

16% 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

  • 2025 - Research.com Rising Stars Award

Overview

Wojciech Marian Czarnecki is affiliated with Google in the United States and has contributed extensively to the field of computer science, with a strong focus on artificial intelligence. Their research spans multiple subfields including artificial intelligence, economics and econometrics, management science and operations research, safety research, and sociology and political science.

Their recent publications demonstrate a consistent engagement with topics related to reinforcement learning, robotics, and multi-agent systems. Notable papers include:

  • Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver, 2023, arXiv (Cornell University)
  • Distral: Robust Multitask Reinforcement Learning, 2025, Oxford University Research Archive (ORA) (University of Oxford)
  • From motor control to team play in simulated humanoid football, 2022, Science Robotics
  • Discovering Reinforcement Learning Algorithms, 2020, arXiv (Cornell University)
  • Open-Ended Learning Leads to Generally Capable Agents, 2021, arXiv (Cornell University)

Their work frequently appears in the following publication venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Science Robotics
  • Artificial Intelligence
  • Oxford University Research Archive (ORA) (University of Oxford)

Research topics covered by Czarnecki include:

  • Reinforcement Learning in Robotics
  • Sports Analytics and Performance
  • Adversarial Robustness in Machine Learning
  • Artificial Intelligence in Games
  • Data Stream Mining Techniques
  • Multi-Agent Systems and Negotiation
  • Experimental Behavioral Economics Studies

Frequent coauthors include Thore Graepel, Karl Tuyls, Nicolas Heess, Guy Lever, and Shayegan Omidshafiei, indicating collaboration networks that span expertise in machine learning and artificial intelligence.

Their research contributes predominantly to the areas of reinforcement learning and robotics, with applications extending to sports analytics and multi-agent systems. These interdisciplinary engagements reflect an integration of computational methods with behavioral and economic studies.

Best Publications

  • Grandmaster level in StarCraft II using multi-agent reinforcement learning.

    Oriol Vinyals;Igor Babuschkin;Wojciech M. Czarnecki;Michaël Mathieu

  • Reinforcement Learning with Unsupervised Auxiliary Tasks

    Max Jaderberg;Volodymyr Mnih;Wojciech Marian Czarnecki;Tom Schaul

  • On Loss Functions for Deep Neural Networks in Classification

    Katarzyna Janocha;Wojciech Marian Czarnecki

  • Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.

    Max Jaderberg;Wojciech M. Czarnecki;Iain Dunning;Luke Marris

  • Value-Decomposition Networks For Cooperative Multi-Agent Learning

    Peter Sunehag;Guy Lever;Audrunas Gruslys;Wojciech Marian Czarnecki

  • Population based training of neural networks

    Maxwell Elliot Jaderberg;Wojciech Czarnecki;Timothy Frederick Goldie Green;Valentin Clement Dalibard

  • Human-level performance in 3D multiplayer games with population-based reinforcement learning

    Max Jaderberg;Wojciech M. Czarnecki;Iain Dunning;Luke Marris

  • Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward

    Peter Sunehag;Guy Lever;Audrunas Gruslys;Wojciech Marian Czarnecki

  • Distral: robust multitask reinforcement learning

    Yee Whye Teh;Victor Bapst;Wojciech Marian Czarnecki;John Quan

  • Progress & Compress: A scalable framework for continual learning

    Jonathan Schwarz;Jelena Luketina;Wojciech M. Czarnecki;Agnieszka Grabska-Barwinska

  • Progress & Compress: A scalable framework for continual learning

    Jonathan Schwarz;Wojciech Czarnecki;Jelena Luketina;Agnieszka Grabska-Barwinska

  • Population Based Training of Neural Networks

    Unknown

  • Decoupled neural interfaces using synthetic gradients

    Max Jaderberg;Wojciech Marian Czarnecki;Simon Osindero;Oriol Vinyals

  • Grounded Language Learning in a Simulated 3D World

    Karl Moritz Hermann;Felix Hill;Simon Green;Fumin Wang

  • Multi-task Deep Reinforcement Learning with PopArt

    Matteo Hessel;Hubert Soyer;Lasse Espeholt;Wojciech Czarnecki

  • Distral: Robust Multitask Reinforcement Learning

    Yee Whye Teh;Victor Bapst;Wojciech Marian Czarnecki;John Quan

  • Adapting Auxiliary Losses Using Gradient Similarity

    Yunshu Du;Wojciech M. Czarnecki;Siddhant M. Jayakumar;Razvan Pascanu

  • Sobolev Training for Neural Networks

    Wojciech Marian Czarnecki;Simon Osindero;Max Jaderberg;Grzegorz Swirszcz

  • α-Rank: Multi-Agent Evaluation by Evolution.

    Shayegan Omidshafiei;Christos H. Papadimitriou;Georgios Piliouras;Karl Tuyls

  • On Loss Functions for Deep Neural Networks in Classification

    Katarzyna Janocha;Wojciech Marian Czarnecki

  • Decoupled Neural Interfaces using Synthetic Gradients

    Max Jaderberg;Wojciech Marian Czarnecki;Simon Osindero;Oriol Vinyals

  • Kickstarting Deep Reinforcement Learning

    Simon Schmitt;Jonathan J. Hudson;Augustin Zidek;Simon Osindero

  • From Motor Control to Team Play in Simulated Humanoid Football.

    Siqi Liu;Guy Lever;Zhe Wang;Josh Merel

  • Open-ended learning in symmetric zero-sum games

    David Balduzzi;Marta Garnelo;Yoram Bachrach;Wojciech M. Czarnecki

  • Multiplicative Interactions and Where to Find Them

    Siddhant M. Jayakumar;Jacob Menick;Wojciech M. Czarnecki;Jonathan Schwarz

  • Distilling Policy Distillation

    Wojciech Marian Czarnecki;Razvan Pascanu;Simon Osindero;Siddhant M. Jayakumar

  • Discovering Reinforcement Learning Algorithms

    Junhyuk Oh;Matteo Hessel;Wojciech M. Czarnecki;Zhongwen Xu

Frequent Co-Authors

Razvan Pascanu
Razvan Pascanu DeepMind (United Kingdom)
Joel Z. Leibo
Joel Z. Leibo DeepMind (United Kingdom)
Thore Graepel
Thore Graepel University College London
Koray Kavukcuoglu
Koray Kavukcuoglu DeepMind (United Kingdom)
Karl Tuyls
Karl Tuyls DeepMind (United Kingdom)
David Silver
David Silver DeepMind (United Kingdom)
Yoram Bachrach
Yoram Bachrach DeepMind (United Kingdom)
Yee Whye Teh
Yee Whye Teh University of Oxford
Nicolas Heess
Nicolas Heess DeepMind (United Kingdom)
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA

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