World's Best Scientists 2026 revealed!
Christian Sohler

Christian Sohler

D-Index & Metrics

Computer Science

D-Index
42
Citations
5721
World Ranking
8522
National Ranking
420

Christian Sohler 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 Christian Sohler 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: 155 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Christian Sohler 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 Christian Sohler 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Christian Sohler is affiliated with the University of Cologne in Germany and specializes in the field of computer science, with a focus on artificial intelligence, computer vision and pattern recognition, computational theory and mathematics, computational mechanics, and statistical and nonlinear physics. Their work covers a diverse range of topics including advanced clustering algorithms research, stochastic gradient optimization techniques, sparse and compressive sensing techniques, face and expression recognition, privacy-preserving technologies in data, data stream mining techniques, and machine learning and algorithms.

Notable recent papers authored or coauthored by Christian Sohler include:

  • Turning Big Data Into Tiny Data: Constant-Size Coresets for k-Means, PCA, and Projective Clustering, 2020, SIAM Journal on Computing
  • Streaming statistical models via Merge & Reduce, 2020, International Journal of Data Science and Analytics
  • Fast and Accurate k-means++ via Rejection Sampling, 2020, arXiv (Cornell University)
  • Testable Properties in General Graphs and Random Order Streaming, 2020, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Sublinear Time Approximation of the Cost of a Metric k-Nearest Neighbor Graph, 2024, SIAM Journal on Computing

Their publication record shows a frequent presence in respected venues, including:

  • arXiv (Cornell University)
  • SIAM Journal on Computing
  • International Journal of Data Science and Analytics
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)

Christian Sohler collaborates regularly with a number of coauthors, including Michael Kapralov, Melanie Schmidt, Artur Czumaj, Silvio Lattanzi, and Dan Feldman. These collaborations indicate an active engagement in ongoing research networks within their fields of study.

Their research contributions span various subfields, particularly targeting algorithmic approaches to clustering, data streaming, and optimization problems, reflecting an established focus on computational methods and data science applications.

Best Publications

  • StreamKM++: A clustering algorithm for data streams

    Marcel R. Ackermann;Marcus Märtens;Christoph Raupach;Kamil Swierkot

  • Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering

    Dan Feldman;Melanie Schmidt;Christian Sohler

  • Counting triangles in data streams

    Luciana S. Buriol;Gereon Frahling;Stefano Leonardi;Alberto Marchetti-Spaccamela

  • A FAST k-MEANS IMPLEMENTATION USING CORESETS

    Gereon Frahling;Christian Sohler

  • Randomized Pursuit-Evasion in Graphs

    Micah Adler;Harald Räcke;Naveen Sivadasan;Christian Sohler

  • A PTAS for k-means clustering based on weak coresets

    Dan Feldman;Morteza Monemizadeh;Christian Sohler

  • Testing expansion in bounded-degree graphs

    Artur Czumaj;Christian Sohler

  • Clustering for metric and nonmetric distance measures

    Marcel R. Ackermann;Johannes Blömer;Christian Sohler

  • Coresets in dynamic geometric data streams

    Gereon Frahling;Christian Sohler

  • Every Property of Hyperfinite Graphs Is Testable

    Ilan Newman;Christian Sohler

  • SAMPLING IN DYNAMIC DATA STREAMS AND APPLICATIONS

    Gereon Frahling;Piotr Indyk;Christian Sohler

  • Analysis of Agglomerative Clustering

    Marcel Rudolf Ackermann;Johannes Blömer;Daniel Kuntze;Christian Sohler

  • Theoretical Analysis of the k -Means Algorithm – A Survey

    Johannes Blömer;Christiane Lammersen;Melanie Schmidt;Christian Sohler

  • Sampling in dynamic data streams and applications

    Gereon Frahling;Piotr Indyk;Christian Sohler

  • Estimating the Weight of Metric Minimum Spanning Trees in Sublinear Time

    Artur Czumaj;Christian Sohler

  • Coresets and sketches for high dimensional subspace approximation problems

    Dan Feldman;Morteza Monemizadeh;Christian Sohler;David P. Woodruff

  • Encoding a triangulation as a permutation of its point set.

    Markus Denny;Christian Sohler

  • BICO: BIRCH Meets Coresets for k-Means Clustering

    Hendrik Fichtenberger;Marc Gillé;Melanie Schmidt;Chris Schwiegelshohn

  • Subspace embeddings for the L1-norm with applications

    Christian Sohler;David P. Woodruff

  • Fair Coresets and Streaming Algorithms for Fair k-means

    Melanie Schmidt;Chris Schwiegelshohn;Christian Sohler

  • StreamKM++: a clustering algorithm for data streams

    Marcel R. Ackermann;Christiane Lammersen;Marcus Märtens;Christoph Raupach

  • Clustering for Metric and Non-Metric Distance Measures ⁄ (full version)

    Marcel R. Ackermann;Johannes Bl;Christian Sohler

Frequent Co-Authors

Artur Czumaj
Artur Czumaj University of Warwick
David P. Woodruff
David P. Woodruff Carnegie Mellon University
Christian Scheideler
Christian Scheideler University of Paderborn
C. Seshadhri
C. Seshadhri University of California, Santa Cruz
Oded Goldreich
Oded Goldreich Weizmann Institute of Science
Dana Ron
Dana Ron Tel Aviv University
Lance Fortnow
Lance Fortnow Illinois Institute of Technology
Berthold Vöcking
Berthold Vöcking RWTH Aachen University

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