World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
12660
World Ranking
3650
National Ranking
163

Volker Markl 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 Volker Markl 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: 319 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Volker Markl 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 Volker Markl 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: 58 D-Index — 75th percentile

75% 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

  • 2020 - ACM Fellow For contributions to query optimization, scalable data processing, and data programmability

Overview

Volker Markl is affiliated with the Technical University of Berlin in Germany. Their research primarily spans the field of Computer Science, with extensive work in related subfields such as Computer Networks and Communications, Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, and Signal Processing.

The main topics of their research include Advanced Database Systems and Queries, Cloud Computing and Resource Management, Data Stream Mining Techniques, Data Management and Algorithms, Parallel Computing and Optimization Techniques, Advanced Data Storage Technologies, and Scientific Computing and Data Management.

Volker Markl has published numerous papers in several frequent venues, including:

  • Proceedings of the VLDB Endowment
  • arXiv (Cornell University)
  • ACM SIGMOD Record
  • Proceedings of the ACM on Management of Data
  • The VLDB Journal

Selected recent papers authored or co-authored by Volker Markl include:

  • The Seattle Report on Database Research, 2020, ACM SIGMOD Record
  • Continuous Training and Deployment of Deep Learning Models, 2021, Datenbank-Spektrum
  • Query Processing on Heterogeneous CPU/GPU Systems, 2022, ACM Computing Surveys
  • Artificial intelligence to advance Earth observation: A review of models, recent trends, and pathways forward, 2023, arXiv (Cornell University)
  • The Seattle report on database research, 2022, Communications of the ACM

Frequent collaborators in their research include Jorge-Arnulfo Quiané-Ruiz, Zoi Kaoudi, Steffen Zeuch, Eleni Tzirita Zacharatou, and Tilmann Rabl.

In recognition of their contributions, Volker Markl was named an ACM Fellow in 2020 for work related to query optimization, scalable data processing, and data programmability.

Best Publications

  • Apache flink : Stream and batch processing in a single engine

    Paris Carbone;Paris Carbone;Asterios Katsifodimos;Asterios Katsifodimos;Stephan Ewen;Volker Markl;Volker Markl

  • The Stratosphere platform for big data analytics

    Alexander Alexandrov;Rico Bergmann;Stephan Ewen;Johann-Christoph Freytag

  • LEO - DB2's LEarning Optimizer

    Michael Stillger;Guy M. Lohman;Volker Markl;Mokhtar Kandil

  • Bigearthnet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding

    Gencer Sumbul;Marcela Charfuelan;Begum Demir;Volker Markl

  • CORDS: automatic discovery of correlations and soft functional dependencies

    Ihab F. Ilyas;Volker Markl;Peter Haas;Paul Brown

  • Nephele/PACTs: a programming model and execution framework for web-scale analytical processing

    Dominic Battré;Stephan Ewen;Fabian Hueske;Odej Kao

  • Robust query processing through progressive optimization

    Volker Markl;Vijayshankar Raman;David Simmen;Guy Lohman

  • Benchmarking Distributed Stream Data Processing Systems

    Jeyhun Karimov;Tilmann Rabl;Asterios Katsifodimos;Roman Samarev

  • Integrating the UB-Tree into a Database System Kernel

    Frank Ramsak;Volker Markl;Robert Fenk;Martin Zirkel

  • The Beckman report on database research

    Daniel Abadi;Rakesh Agrawal;Anastasia Ailamaki;Magdalena Balazinska

  • Query Expansion

    Unknown

  • Hardware-oblivious parallelism for in-memory column-stores

    Max Heimel;Michael Saecker;Holger Pirk;Stefan Manegold

  • BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval.

    Gencer Sumbul;Arne de Wall;Tristan Kreuziger;Filipe Marcelino

  • LEO: An autonomic query optimizer for DB2

    V. Markl;G. M. Lohman;V. Raman

  • Learning from empirical results in query optimization

    Guy Maring Lohman;Michael Stillger;Volker Markl

  • Damia: data mashups for intranet applications

    David E. Simmen;Mehmet Altinel;Volker Markl;Sriram Padmanabhan

  • Damia: a data mashup fabric for intranet applications

    Mehmet Altinel;Paul Brown;Susan Cline;Rajesh Kartha

  • Automatically and adaptively determining execution plans for queries with parameter markers

    Wei Fan;Guy Maring Lohman;Volker Gerhard Markl;Nimrod Megiddo

  • Improving OLAP performance by multidimensional hierarchical clustering

    V. Markl;F. Ramsak;R. Bayer

  • Progressive refinement of a federated query plan during query execution

    Stephan Eberhard Ewen;Holger Kache;Volker Gerhard Markl;Vijayshankar Raman

  • Spinning fast iterative data flows

    Stephan Ewen;Kostas Tzoumas;Moritz Kaufmann;Volker Markl

  • Big Data: Eine interdisziplinäre Chance für die Wirtschaftsinformatik

    Michael Schermann;Holmer Hemsen;Christoph Buchmüller;Till Bitter

Frequent Co-Authors

Peter J. Haas
Peter J. Haas University of Massachusetts Amherst
Guy M. Lohman
Guy M. Lohman IBM (United States)
Vijayshankar Raman
Vijayshankar Raman Google (United States)
Nimrod Megiddo
Nimrod Megiddo IBM (United States)
Odej Kao
Odej Kao Technical University of Berlin
Ashraf Aboulnaga
Ashraf Aboulnaga The University of Texas at Arlington
Ihab F. Ilyas
Ihab F. Ilyas University of Waterloo
Donald Kossmann
Donald Kossmann Microsoft (United States)
Sam Lightstone
Sam Lightstone IBM (United States)
Gunter Saake
Gunter Saake Otto-von-Guericke University Magdeburg

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to a range of rewarding online degrees and career options. Many students seek flexible learning options, and online programs make it easier to balance education with work or family commitments.

Business-minded students might benefit from an online mba, which equips graduates for leadership roles in tech companies and startups. If you’re seeking a shorter time commitment, check out one year graduate programs for fast-tracked academic advancement in related fields.

Career changers or those eager to enter the workforce quickly can explore the fastest degree to get—many technology-oriented programs deliver both a strong return on investment and rapid job placement.

With the rise of artificial intelligence, choosing one of the best online ai degree programs can lead to high-demand careers in AI, data science, and machine learning.

No matter your interests, there’s a pathway in online education to help you reach your career goals in the evolving tech landscape.

Best Scientists Citing Volker Markl

Trending Scientists