World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
5124
World Ranking
13516
National Ranking
650

Felix Wolf 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 Felix Wolf 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: 296 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Felix Wolf 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 Felix Wolf 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: 31 D-Index — 6th percentile

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

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

Overview

Felix Wolf is affiliated with the Technical University of Darmstadt in Germany. Their primary research domain lies within computer science, with a focus on several subfields including computer networks and communications, hardware and architecture, information systems, electrical and electronic engineering, and cellular and molecular neuroscience.

Their academic work extensively covers topics such as parallel computing and optimization techniques, advanced data storage technologies, cloud computing and resource management, distributed and parallel computing systems, software system performance and reliability, distributed systems and fault tolerance, as well as neural dynamics and brain function.

Frequent coauthors collaborating with Felix Wolf include Fabian Czappa, Alexandru Calotoiu, Marvin Kaster, Torsten Hoefler, and Markus Butz-Ostendorf.

Felix Wolf has contributed a number of publications in notable academic venues. Their frequent publication outlets include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Parallel Computing
  • Journal of Parallel and Distributed Computing
  • Frontiers in Neuroinformatics

Significant papers authored or coauthored by Felix Wolf are as follows:

  • Malleability in Modern HPC Systems: Current Experiences, Challenges, and Future Opportunities, 2024, IEEE Transactions on Parallel and Distributed Systems
  • Phosphorylation-Dependent Differences in CXCR4-LASP1-AKT1 Interaction between Breast Cancer and Chronic Myeloid Leukemia, 2020, Cells
  • Influence of Noisy Environments on Behavior of HPC Applications, 2021, Lobachevskii Journal of Mathematics
  • Insights into the Cellular and Molecular Mechanisms behind the Antifibrotic Effects of Nerandomilast, 2025, American Journal of Respiratory Cell and Molecular Biology
  • Simulation of thermally sprayed coating properties considering the splat boundaries, 2021, IOP Conference Series Materials Science and Engineering

Felix Wolf has contributed to book publications through Springer Science+Business Media with at least one title titled Benchmarking, Measuring, and Optimizing, published in 2021.

Best Publications

  • The Scalasca performance toolset architecture

    Markus Geimer;Felix Wolf;Brian J. N. Wylie;Erika Ábrahám

  • Score-P: A Joint Performance Measurement Run-Time Infrastructure for Periscope, Scalasca, TAU, and Vampir

    Andreas Knüpfer;Christian Rössel;Dieter an Mey;Scott Biersdorff

  • The Scalasca performance toolset architecture

    Unknown

  • Automatic performance analysis of hybrid MPI/OpenMP applications

    F. Wolf;B. Mohr

  • Using automated performance modeling to find scalability bugs in complex codes

    Alexandru Calotoiu;Torsten Hoefler;Marius Poke;Felix Wolf

  • KOJAK – A Tool Set for Automatic Performance Analysis of Parallel Programs

    Bernd Mohr;Felix Wolf

  • Design and Prototype of a Performance Tool Interface for OpenMP

    Bernd Mohr;Allen D. Malony;Sameer Shende;Felix Wolf

  • Scalable parallel trace-based performance analysis

    Markus Geimer;Felix Wolf;Brian J. N. Wylie;Bernd Mohr

  • Open Trace Format 2: The Next Generation of Scalable Trace Formats and Support Libraries.

    Dominic Eschweiler;Michael Wagner;Markus Geimer;Andreas Knüpfer

  • Scalable massively parallel I/O to task-local files

    Wolfgang Frings;Felix Wolf;Ventsislav Petkov

  • Score-P: A Unified Performance Measurement System for Petascale Applications

    Dieter an Mey;Scott Biersdorf;Christian Bischof;Kai Diethelm

  • Usage of the SCALASCA toolset for scalable performance analysis of large-scale parallel applications

    Felix Wolf;Felix Wolf;Brian J N Wylie;Erika Ábrahám;Daniel Becker;Daniel Becker

  • Identifying the Root Causes of Wait States in Large-Scale Parallel Applications

    David Böhme;Markus Geimer;Lukas Arnold;Felix Voigtlaender

  • Towards a Performance Tool Interface for OpenMP: An Approach based on Directive Rewriting

    Bernd Mohr;Allen Malony;Sameer Shende;Felix Wolf

  • Interoperation of world-wide production e-Science infrastructures

    M. Riedel;E. Laure;Th. Soddemann;L. Field

  • Scalable Critical-Path Based Performance Analysis

    David Bohme;Felix Wolf;Bronis R. de Supinski;Martin Schulz

  • KOJAK - A Tool Set for Automatic Performance Analysis of Parallel Applications

    Felix Wolf;Bernd Mohr

  • A scalable tool architecture for diagnosing wait states in massively parallel applications

    Markus Geimer;Felix Wolf;Brian J. N. Wylie;Bernd Mohr

  • An algebra for cross-experiment performance analysis

    F. Song;F. Wolf;N. Bhatia;J. Dongarra

  • Fast Multi-parameter Performance Modeling

    Alexandru Calotoiu;David Beckinsale;Christopher W. Earl;Torsten Hoefler

  • Identifying the Root Causes of Wait States in Large-Scale Parallel Applications

    David Bohme;Markus Geimer;Felix Wolf;Lukas Arnold

  • Automatic Performance Analysis of MPI Applications Based on Event Traces

    Felix Wolf;Bernd Mohr

  • EARL - A Programmable and Extensible Toolkit for Analyzing Event Traces of Message Passing Programs

    Felix Wolf;Bernd Mohr

Frequent Co-Authors

Christian Bischof
Christian Bischof Technical University of Darmstadt
Allen D. Malony
Allen D. Malony University of Oregon
Jack Dongarra
Jack Dongarra University of Tennessee at Knoxville
Helmut Harbrecht
Helmut Harbrecht University of Basel
Walter F. Tichy
Walter F. Tichy Karlsruhe Institute of Technology
Mohammad Norouzi
Mohammad Norouzi Google (United States)
Martin Schulz
Martin Schulz Technical University of Munich

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