World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
71
Citations
28945
World Ranking
1738
National Ranking
12

Thomas Pock 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 Thomas Pock 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: 241 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Thomas Pock 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 Thomas Pock 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: 71 D-Index — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Overview

Thomas Pock is affiliated with Graz University of Technology in Austria and has made substantial contributions across several interrelated fields. Their research primarily spans computer science, medicine, and engineering, with a focus on advanced computational methods applied to medical imaging and image processing.

Their work encompasses key subfields such as computer vision and pattern recognition, radiology, nuclear medicine and imaging, artificial intelligence, cardiology and cardiovascular medicine, and computational mechanics. The integration of these areas reflects a multidisciplinary approach to medical technology and imaging sciences.

Main topics addressed in their research include sparse and compressive sensing techniques, medical image segmentation techniques, medical imaging techniques and applications, image and signal denoising methods, advanced MRI techniques and applications, advanced vision and imaging, and advanced image processing techniques.

Their publication record is extensive, with a notable presence in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Journal of Mathematical Imaging and Vision
  • SIAM Journal on Imaging Sciences
  • SIAM Journal on Mathematics of Data Science
  • IEEE Signal Processing Magazine

Their recent papers illustrate a strong emphasis on deep learning and variational methods applied to MRI reconstruction and cardiac electrophysiology modelling. Selected recent publications include:

  • "Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues" (2020), published in IEEE Signal Processing Magazine
  • "A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs" (2021), published in Medical Image Analysis
  • "Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI" (2023), published in Radiology
  • "Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction" (2021), published in IEEE Transactions on Medical Imaging
  • "Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration" (2020), published in Journal of Mathematical Imaging and Vision

Thomas Pock has collaborated frequently with several researchers, reflecting a network of co-authors contributing to his research domains. Among the most frequent co-authors are Erich Kobler, Alexander Effland, Gernot Plank, Martin Zach, and Antonin Chambolle.

Best Publications

  • A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging

    Antonin Chambolle;Thomas Pock

  • A duality based approach for realtime TV-L 1 optical flow

    C. Zach;T. Pock;H. Bischof

  • Total Generalized Variation

    Kristian Bredies;Karl Kunisch;Thomas Pock

  • Learning a variational network for reconstruction of accelerated MRI data.

    Kerstin Hammernik;Teresa Klatzer;Erich Kobler;Michael P. Recht

  • Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

    Yunjin Chen;Thomas Pock

  • Second order total generalized variation (TGV) for MRI

    Florian Knoll;Kristian Bredies;Thomas Pock;Rudolf Stollberger

  • An Improved Algorithm for TV-L1 Optical Flow

    Andreas Wedel;Thomas Pock;Christopher Zach;Horst Bischof

  • An introduction to Total Variation for Image Analysis

    Antonin Chambolle;Vicent Caselles;Matteo Novaga;Daniel Cremers

  • Anisotropic Huber-L1 Optical Flow

    Manuel Werlberger;Werner Trobin;Thomas Pock;Andreas Wedel

  • Diagonal preconditioning for first order primal-dual algorithms in convex optimization

    Thomas Pock;Antonin Chambolle

  • An introduction to continuous optimization for imaging

    Antonin Chambolle;Thomas Pock

  • PROST: Parallel robust online simple tracking

    Jakob Santner;Christian Leistner;Amir Saffari;Thomas Pock

  • iPiano: Inertial Proximal Algorithm for Nonconvex Optimization

    Peter Ochs;Yunjin Chen;Thomas Brox;Thomas Pock

  • An algorithm for minimizing the Mumford-Shah functional

    Thomas Pock;Daniel Cremers;Horst Bischof;Antonin Chambolle

  • On the ergodic convergence rates of a first-order primal---dual algorithm

    Antonin Chambolle;Thomas Pock

  • An Inertial Forward-Backward Algorithm for Monotone Inclusions

    Dirk A. Lorenz;Thomas Pock

  • On learning optimized reaction diffusion processes for effective image restoration

    Yunjin Chen;Wei Yu;Thomas Pock

  • A Globally Optimal Algorithm for Robust TV-L 1 Range Image Integration

    C. Zach;T. Pock;H. Bischof

  • Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues

    Florian Knoll;Kerstin Hammernik;Chi Zhang;Steen Moeller

  • A convex relaxation approach for computing minimal partitions

    Thomas Pock;Antonin Chambolle;Daniel Cremers;Horst Bischof

  • iPiano: Inertial Proximal Algorithm for Non-Convex Optimization

    Peter Ochs;Yunjin Chen;Thomas Brox;Thomas Pock

Frequent Co-Authors

Horst Bischof
Horst Bischof Graz University of Technology
Florian Knoll
Florian Knoll University of Erlangen-Nuremberg
Daniel Cremers
Daniel Cremers Technical University of Munich
Rene Ranftl
Rene Ranftl Intel (United States)
Antonin Chambolle
Antonin Chambolle Paris Dauphine University
Daniel K. Sodickson
Daniel K. Sodickson New York University
Thomas Brox
Thomas Brox University of Freiburg
Karl Kunisch
Karl Kunisch University of Graz
Kristian Bredies
Kristian Bredies University of Graz

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