World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
13371
World Ranking
7776
National Ranking
132

Christof Monz 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 Christof Monz 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: 157 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Christof Monz 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 Christof Monz 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Christof Monz is affiliated with the University of Amsterdam in the Netherlands and works primarily in the field of Computer Science. Their research focuses extensively on Artificial Intelligence, with significant contributions also in Computer Vision and Pattern Recognition, Computer Science Applications, Health Informatics, and Safety Research.

The scientist's body of work covers several core topics, including:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Text Readability and Simplification
  • Multimodal Machine Learning Applications
  • Speech and dialogue systems
  • Speech Recognition and Synthesis
  • Mobile Crowdsensing and Crowdsourcing

A substantial number of their publications appear on the preprint server arXiv (Cornell University), where they have contributed 33 papers. Other notable publication venues include the Proceedings of the AAAI Conference on Artificial Intelligence, Computer, ACM Transactions on Information Systems, and Data Archiving and Networked Services (DANS).

Their recent papers include:

  • A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence (2020, Computer)
  • Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation (2020, Proceedings of the AAAI Conference on Artificial Intelligence)
  • RefNet: A Reference-Aware Network for Background Based Conversation (2020, Proceedings of the AAAI Conference on Artificial Intelligence)
  • Conversations with Search Engines: SERP-based Conversational Response Generation (2021, ACM Transactions on Information Systems)
  • TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance Generation (2020, arXiv (Cornell University))

Collaborations have been established with several frequent co-authors, including Baohao Liao, Maarten de Rijke, David Stap, Pengjie Ren, and Shaomu Tan.

Best Publications

  • Findings of the 2014 Workshop on Statistical Machine Translation

    Ondrej Bojar;Christian Buck;Christian Federmann;Barry Haddow

  • Findings of the 2015 Workshop on Statistical Machine Translation

    Ondřej Bojar;Rajen Chatterjee;Christian Federmann;Barry Haddow

  • Findings of the 2012 Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Matt Post

  • Findings of the 2009 Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Josh Schroeder

  • Findings of the 2018 Conference on Machine Translation (WMT18)

    Ondřej Bojar;Christian Federmann;Mark Fishel;Yvette Graham

  • Findings of the 2017 Conference on Machine Translation (WMT17)

    Ondřej Bojar;Rajen Chatterjee;Christian Federmann;Yvette Graham

  • Findings of the 2016 Conference on Machine Translation

    Ondˇrej Bojar;Rajen Chatterjee;Christian Federmann;Yvette Graham

  • Data Augmentation for Low-Resource Neural Machine Translation

    Marzieh Fadaee;Arianna Bisazza;Christof Monz

  • Findings of the 2019 Conference on Machine Translation (WMT19)

    Loïc Barrault;Ondřej Bojar;Marta R. Costa-jussà;Christian Federmann

  • Findings of the 2013 Workshop on Statistical Machine Translation

    Ondřej Bojar;Christian Buck;Chris Callison-Burch;Christian Federmann

  • Findings of the 2011 Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Omar Zaidan

  • (Meta-) Evaluation of Machine Translation

    Chris Callison-Burch;Cameron Fordyce;Philipp Koehn;Christof Monz

  • Manual and Automatic Evaluation of Machine Translation between European Languages

    Philipp Koehn;Christof Monz

  • A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence

    Zeynep Akata;Dan Balliet;Maarten de Rijke;Frank Dignum

  • Further Meta-Evaluation of Machine Translation

    Chris Callison-Burch;Cameron Fordyce;Philipp Koehn;Christof Monz

  • Findings of the 2010 Joint Workshop on Statistical Machine Translation and Metrics for Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Kay Peterson

  • Document understanding for a broad class of documents

    Marco Aiello;Christof Monz;Leon Todoran;Marcel Worring

  • Findings of the 2020 Conference on Machine Translation (WMT20)

    Loïc Barrault;Magdalena Biesialska;Ondrej Bojar;Marta R. Costa-jussà

  • The Importance of Being Recurrent for Modeling Hierarchical Structure

    Ke M. Tran;Arianna Bisazza;Christof Monz

  • Dynamic Data Selection for Neural Machine Translation

    Marlies van der Wees;Arianna Bisazza;Christof Monz

  • Proceedings of the Sixth Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Omar F. Zaidan

Frequent Co-Authors

Philipp Koehn
Philipp Koehn Johns Hopkins University
Maarten de Rijke
Maarten de Rijke University of Amsterdam
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Barry Haddow
Barry Haddow University of Edinburgh
Lucia Specia
Lucia Specia Imperial College London
Pengjie Ren
Pengjie Ren Shandong University
Bonnie J. Dorr
Bonnie J. Dorr University of Florida
Jaap Kamps
Jaap Kamps University of Amsterdam
Marco Turchi
Marco Turchi Fondazione Bruno Kessler
Marcel Worring
Marcel Worring University of Amsterdam

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