World's Best Scientists 2026 revealed!
Hans-Arno Jacobsen

Hans-Arno Jacobsen

D-Index & Metrics

Computer Science

D-Index
61
Citations
14954
World Ranking
3073
National Ranking
117

Hans-Arno Jacobsen 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 Hans-Arno Jacobsen 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: 486 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Hans-Arno Jacobsen 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 Hans-Arno Jacobsen 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.

Overview

Hans-Arno Jacobsen is affiliated with the University of Toronto in Canada and has a strong research focus within the field of Computer Science. Their work spans multiple subfields, including Computer Networks and Communications, Artificial Intelligence, Information Systems, Electrical and Electronic Engineering, and Computer Vision and Pattern Recognition.

The scientist's research topics cover a variety of important areas in computing technology. These include Cloud Computing and Resource Management, Blockchain Technology Applications and Security, Distributed Systems and Fault Tolerance, Caching and Content Delivery, Graph Theory and Algorithms, Smart Grid Energy Management, and IoT and Edge/Fog Computing.

Frequent coauthors in their research collaborations include Ruben Mayer, Shashank Motepalli, Herbert Woisetschläger, Gengrui Zhang, and Shiquan Zhang.

Their publications have appeared in numerous venues, with significant contributions to:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Zenodo (CERN European Organization for Nuclear Research)
  • ACM Computing Surveys
  • IEEE Transactions on Knowledge and Data Engineering

The most recent papers published by Hans-Arno Jacobsen illustrate diverse subjects and publication outlets:

  • "Scalable Deep Learning on Distributed Infrastructures," 2020, ACM Computing Surveys
  • "BlockEV: Efficient and Secure Charging Station Selection for Electric Vehicles," 2020, IEEE Transactions on Intelligent Transportation Systems
  • "Reaching Consensus in the Byzantine Empire: A Comprehensive Review of BFT Consensus Algorithms," 2023, ACM Computing Surveys
  • "Demand-Response Games for Peer-to-Peer Energy Trading With the Hyperledger Blockchain," 2021, IEEE Transactions on Systems Man and Cybernetics Systems
  • "Transfer Learning With Time Series Data: A Systematic Mapping Study," 2021, IEEE Access

Best Publications

  • PNUTS: Yahoo!'s hosted data serving platform

    Brian F. Cooper;Raghu Ramakrishnan;Utkarsh Srivastava;Adam Silberstein

  • Filtering algorithms and implementation for very fast publish/subscribe systems

    Françoise Fabret;H. Arno Jacobsen;François Llirbat;Joăo Pereira

  • BigBench: towards an industry standard benchmark for big data analytics

    Ahmad Ghazal;Tilmann Rabl;Minqing Hu;Francois Raab

  • Solving big data challenges for enterprise application performance management

    Tilmann Rabl;Sergio Gómez-Villamor;Mohammad Sadoghi;Victor Muntés-Mulero

  • Composite subscriptions in content-based publish/subscribe systems

    Guoli Li;Hans-Arno Jacobsen

  • Caching in video CDNs: building strong lines of defense

    Kianoosh Mokhtarian;Hans-Arno Jacobsen

  • A distributed service-oriented architecture for business process execution

    Guoli Li;Vinod Muthusamy;Hans-Arno Jacobsen

  • Building content-based publish/subscribe systems with distributed hash tables

    David Tam;Reza Azimi;Hans-Arno Jacobsen

  • Using publish/subscribe middleware for mobile systems

    Gianpaolo Cugola;H.-Arno Jacobsen

  • Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques, and Tools

    Ruben Mayer;Hans-Arno Jacobsen

  • The PADRES Distributed Publish/Subscribe System.

    E. Fidler;Hans-Arno Jacobsen;Guoli Li;Serge Mankovski

  • Filtering Algorithms and Implementation for Very Fast Publish/Subscribe.

    Françoise Fabret;Hans-Arno Jacobsen;François Llirbat;João L. M. Pereira

  • A Unified Approach to Routing, Covering and Merging in Publish/Subscribe Systems Based on Modified Binary Decision Diagrams

    Guoli Li;Shuang Hou;H.-A. Jacobsen

  • Quantifying aspects in middleware platforms

    Charles Zhang;Hans-Arno. Jacobsen

  • S-ToPSS: semantic Toronto publish/subscribe system

    Milenko Petrovic;Ioana Burcea;Hans-Arno Jacobsen

  • Distributed Convex Optimization for Electric Vehicle Aggregators

    Jose Rivera;Christoph Goebel;Hans-Arno Jacobsen

  • The PADRES Publish/Subscribe System

    Hans-Arno Jacobsen;Alex King Yeung Cheung;Guoli Li;Balasubramaneyam Maniymaran

  • Resolving feature convolution in middleware systems

    Charles Zhang;Hans-Arno Jacobsen

  • Towards Dependable, Scalable, and Pervasive Distributed Ledgers with Blockchains

    Kaiwen Zhang;Hans-Arno Jacobsen

  • Mobile awareness in a wide area wireless network of info-stations

    Tao Ye;H.-Arno Jacobsen;Randy Katz

  • BE-tree: an index structure to efficiently match boolean expressions over high-dimensional discrete space

    Mohammad Sadoghi;Hans-Arno Jacobsen

  • Solving Big Data Challenges for Enterprise Application Performance Management

    Tilmann Rabl;Mohammad Sadoghi;Hans-Arno Jacobsen;Sergio Gómez-Villamor

Frequent Co-Authors

Haifeng Liu
Haifeng Liu Tianjin University
Bettina Kemme
Bettina Kemme McGill University
Haibing Guan
Haibing Guan Shanghai Jiao Tong University
Oliver Günther
Oliver Günther University of Potsdam
Hartmut Schmeck
Hartmut Schmeck Karlsruhe Institute of Technology
John Mylopoulos
John Mylopoulos University of Ottawa
Dennis Shasha
Dennis Shasha New York University
Sheila A. McIlraith
Sheila A. McIlraith University of Toronto
Christof Weinhardt
Christof Weinhardt Karlsruhe Institute of Technology
Dirk Neumann
Dirk Neumann University of Freiburg

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