World's Best Scientists 2026 revealed!
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Computer Science
Switzerland
2025

D-Index & Metrics

Computer Science

D-Index
61
Citations
25968
World Ranking
2997
National Ranking
140

Karsten M. Borgwardt 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 Karsten M. Borgwardt 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: 183 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Karsten M. Borgwardt 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 Karsten M. Borgwardt 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: 61 D-Index — 79th percentile

79% 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 Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Karsten M. Borgwardt is affiliated with ETH Zurich in Switzerland and has contributed extensively to research across several interconnected fields. Their work spans biochemistry, genetics and molecular biology, medicine, and computer science, with a notable focus on molecular biology, artificial intelligence, epidemiology, genetics, and infectious diseases.

The scientist's research covers a range of topics, including sepsis diagnosis and treatment, machine learning in healthcare, bioinformatics and genomic networks, advanced graph neural networks, bacterial identification and susceptibility testing, gene expression and cancer classification, and genetic associations and epidemiology.

Karsten M. Borgwardt has published in numerous high-profile venues. The most frequent publication outlets include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Bioinformatics, Nature Communications, and Faculty Opinions - Post-Publication Peer Review of the Biomedical Literature.

Coauthor collaborations have been significant in their research, with frequent collaborators including Bastian Rieck, Dexiong Chen, Max Horn, Michael Moor, and Adrian Egli.

Selected recent papers by Karsten M. Borgwardt include:

  • Early prediction of circulatory failure in the intensive care unit using machine learning, 2020, Nature Medicine
  • Persistent complement dysregulation with signs of thromboinflammation in active Long Covid, 2024, Science
  • Biological network analysis with deep learning, 2020, Briefings in Bioinformatics
  • Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning, 2022, Nature Medicine
  • Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review, 2020, Clinical Microbiology and Infection

Best Publications

  • A kernel two-sample test

    Arthur Gretton;Karsten M. Borgwardt;Malte J. Rasch;Bernhard Schölkopf

  • A Kernel Method for the Two-Sample-Problem

    Arthur Gretton;Karsten M. Borgwardt;Malte Rasch;Bernhard Schölkopf

  • Correcting Sample Selection Bias by Unlabeled Data

    Jiayuan Huang;Arthur Gretton;Karsten M. Borgwardt;Bernhard Schölkopf

  • Weisfeiler-Lehman Graph Kernels

    Nino Shervashidze;Pascal Schweitzer;Erik Jan van Leeuwen;Kurt Mehlhorn

  • Integrating structured biological data by Kernel Maximum Mean Discrepancy

    Karsten M. Borgwardt;Arthur Gretton;Malte J. Rasch;Hans-Peter Kriegel

  • Protein function prediction via graph kernels

    Karsten M. Borgwardt;Cheng Soon Ong;Stefan Schönauer;S. V. N. Vishwanathan

  • Graph Kernels

    S. V. N. Vishwanathan;Nicol N. Schraudolph;Risi Kondor;Karsten M. Borgwardt

  • Shortest-path kernels on graphs

    K.M. Borgwardt;H.P. Kriegel

  • Efficient Graphlet Kernels for Large Graph Comparison

    Nino Sherashidze;S. V. N. Vishwanathan;Tobias H. Petri;Kurt Mehlhorn

  • Correcting sample selection bias by unlabeled data

    J Huang;AJ Smola;A Gretton;KM Borgwardt

  • Covariate Shift by Kernel Mean Matching

    A Gretton;AJ Smola;J Huang;M Schmittfull

  • Feature selection via dependence maximization

    Le Song;Alex Smola;Arthur Gretton;Justin Bedo

  • Supervised feature selection via dependence estimation

    Le Song;Alex Smola;Arthur Gretton;Karsten M. Borgwardt

  • Arabidopsis Defense against Botrytis cinerea: Chronology and Regulation Deciphered by High-Resolution Temporal Transcriptomic Analysis

    Oliver P. Windram;Priyadharshini Madhou;Stuart McHattie;Claire Hill

  • The Evaluation of Tools Used to Predict the Impact of Missense Variants Is Hindered by Two Types of Circularity

    Dominik G. Grimm;Dominik G. Grimm;Dominik G. Grimm;Chloé-Agathe Azencott;Fabian Aicheler;Fabian Aicheler;Udo Gieraths

  • Early prediction of circulatory failure in the intensive care unit using machine learning.

    Stephanie L. Hyland;Martin Faltys;Matthias Hüser;Matthias Hüser;Xinrui Lyu;Xinrui Lyu

  • Fast subtree kernels on graphs

    Nino Shervashidze;Karsten M. Borgwardt

  • Future trends in data mining

    Hans-Peter Kriegel;Karsten M. Borgwardt;Peer Kröger;Alexey Pryakhin

  • Biological network analysis with deep learning.

    Giulia Muzio;Leslie O'Bray;Karsten M. Borgwardt

  • Fast Computation of Graph Kernels

    Karsten M. Borgwardt;Nicol N. Schraudolph;S.v.n. Vishwanathan

  • Metropolis Algorithms for Representative Subgraph Sampling

    C. Hubler;H.-P. Kriegel;K. Borgwardt;Z. Ghahramani

  • An introduction to Gaussian processes

    O Stegle;KM Borgwardt

Frequent Co-Authors

Oliver Stegle
Oliver Stegle German Cancer Research Center
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Arthur Gretton
Arthur Gretton University College London
Detlef Weigel
Detlef Weigel Max Planck Institute for Developmental Biology
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Hans-Peter Kriegel
Hans-Peter Kriegel Ludwig-Maximilians-Universität München
Le Song
Le Song Mohamed bin Zayed University of Artificial Intelligence
S. V. N. Vishwanathan
S. V. N. Vishwanathan Purdue University West Lafayette
Gunnar Rätsch
Gunnar Rätsch ETH Zurich
Zoubin Ghahramani
Zoubin Ghahramani University of Cambridge

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