World's Best Scientists 2026 revealed!
Jost Tobias Springenberg

Jost Tobias Springenberg

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
38
Citations
21500
World Ranking
709
National Ranking
18

Computer Science

D-Index
39
Citations
20116
World Ranking
9468
National Ranking
469

Jost Tobias Springenberg 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 Jost Tobias Springenberg 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: 74 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Jost Tobias Springenberg 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 Jost Tobias Springenberg 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: 39 D-Index — 33rd percentile

33% 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

Jost Tobias Springenberg is affiliated with the University of Freiburg in Germany. The primary field of study for Springenberg is Computer Science, with a focus on several subfields including Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Management Science and Operations Research, as well as Control and Systems Engineering.

Springenberg's research topics cover a range of areas within these fields. The main topics of work include:

  • Reinforcement Learning in Robotics
  • Adaptive Dynamic Programming Control
  • Adversarial Robustness in Machine Learning
  • Robot Manipulation and Learning
  • Multimodal Machine Learning Applications
  • Natural Language Processing Techniques
  • Evolutionary Algorithms and Applications

The scientist has contributed to various research papers, primarily published in recognized venues such as arXiv (Cornell University) and the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Recent papers include:

  • "Critic Regularized Regression," 2020, arXiv (Cornell University)
  • "A Generalist Agent," 2022, arXiv (Cornell University)
  • "Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning," 2020, arXiv (Cornell University)
  • "Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics," 2020, arXiv (Cornell University)

Springenberg frequently collaborates with a group of co-authors, including:

  • Martin Riedmiller
  • Nicolas Heess
  • Abbas Abdolmaleki
  • Thomas Lampe
  • Roland Hafner

This collaboration pattern suggests engagement with other researchers who have contributed widely to artificial intelligence and robotics domains. The corpus of work demonstrates repeated exploration of reinforcement learning methodologies aimed at robotic applications, as well as theoretical aspects related to dynamic programming and machine learning robustness.

Best Publications

  • Striving for Simplicity: The All Convolutional Net

    Jost Tobias Springenberg;Alexey Dosovitskiy;Thomas Brox;Martin A. Riedmiller

  • Deep learning with convolutional neural networks for EEG decoding and visualization.

    Robin Tibor Schirrmeister;Jost Tobias Springenberg;Lukas Dominique Josef Fiederer;Martin Glasstetter

  • Auto-sklearn: Efficient and Robust Automated Machine Learning

    Matthias Feurer;Aaron Klein;Katharina Eggensperger;Jost Tobias Springenberg

  • Efficient and robust automated machine learning

    Matthias Feurer;Aaron Klein;Katharina Eggensperger;Jost Tobias Springenberg

  • Discriminative Unsupervised Feature Learning with Convolutional Neural Networks

    Alexey Dosovitskiy;Jost Tobias Springenberg;Martin Riedmiller;Thomas Brox

  • Learning to generate chairs with convolutional neural networks

    Alexey Dosovitskiy;Jost Tobias Springenberg;Thomas Brox

  • Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks

    Alexey Dosovitskiy;Philipp Fischer;Jost Tobias Springenberg;Martin Riedmiller

  • Multimodal deep learning for robust RGB-D object recognition

    Andreas Eitel;Jost Tobias Springenberg;Luciano Spinello;Martin Riedmiller

  • Embed to control: a locally Linear Latent dynamics model for control from raw images

    Manuel Watter;Jost Tobias Springenberg;Joschka Boedecker;Martin Riedmiller

  • Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves

    Tobias Domhan;Jost Tobias Springenberg;Frank Hutter

  • A Generalist Agent

    Unknown

  • Initializing bayesian hyperparameter optimization via meta-learning

    Matthias Feurer;Jost Tobias Springenberg;Frank Hutter

  • Graph Networks as Learnable Physics Engines for Inference and Control

    Alvaro Sanchez-Gonzalez;Nicolas Heess;Jost Tobias Springenberg;Josh Merel

  • Bayesian optimization with robust Bayesian neural networks

    Jost Tobias Springenberg;Aaron Klein;Stefan Falkner;Frank Hutter

  • Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

    Jost Tobias Springenberg

  • Learning by Playing - Solving Sparse Reward Tasks from Scratch

    Martin A. Riedmiller;Roland Hafner;Thomas Lampe;Michael Neunert

  • Learning to Generate Chairs, Tables and Cars with Convolutional Networks

    Alexey Dosovitskiy;Jost Tobias Springenberg;Maxim Tatarchenko;Thomas Brox

  • Maximum a Posteriori Policy Optimisation

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

  • Deep reinforcement learning with successor features for navigation across similar environments

    Jingwei Zhang;Jost Tobias Springenberg;Joschka Boedecker;Wolfram Burgard

  • Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

    Jost Tobias Springenberg

  • Learning an Embedding Space for Transferable Robot Skills

    Karol Hausman;Jost Tobias Springenberg;Ziyu Wang;Nicolas Heess

  • Critic Regularized Regression

    Ziyu Wang;Alexander Novikov;Konrad Zolna;Jost Tobias Springenberg

  • Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning

    Noah Siegel;Jost Tobias Springenberg;Felix Berkenkamp;Abbas Abdolmaleki

Frequent Co-Authors

Martin Riedmiller
Martin Riedmiller DeepMind (United Kingdom)
Nicolas Heess
Nicolas Heess DeepMind (United Kingdom)
Frank Hutter
Frank Hutter University of Freiburg
Alexey Dosovitskiy
Alexey Dosovitskiy Google (United States)
Thomas Brox
Thomas Brox University of Freiburg
Wolfram Burgard
Wolfram Burgard University of Technology Nuremberg
Raia Hadsell
Raia Hadsell DeepMind (United Kingdom)
Francesco Nori
Francesco Nori DeepMind (United Kingdom)
Yuval Tassa
Yuval Tassa Google (United States)
Jonas Buchli
Jonas Buchli DeepMind (United Kingdom)

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