World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
16573
World Ranking
9943
National Ranking
20

Overview

Ondrej Bojar is a researcher primarily affiliated with Charles University in Czech Republic. Their academic work centers largely on computer science, with a significant focus on artificial intelligence and its applications. The researcher has contributed to various subfields, including computer vision and pattern recognition, language and linguistics, signal processing, and information systems.

Their research topics cover a broad range of areas such as natural language processing techniques, topic modeling, speech recognition and synthesis, speech and dialogue systems, multimodal machine learning applications, text readability and simplification, and translation studies and practices.

Boasting a substantial number of publications, Ondrej Bojar's research has appeared in diverse venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • The Prague Bulletin of Mathematical Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Natural language processing.
  • Nature Communications

Recent papers authored or co-authored by Ondrej Bojar illustrate the scope and impact of their contributions:

  • Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals, 2020, Nature Communications
  • Sequence Length is a Domain: Length-based Overfitting in Transformer Models, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Announcing CzEng 2.0 Parallel Corpus with over 2 Gigawords, 2020, arXiv (Cornell University)
  • Neural Machine Translation Quality and Post-Editing Performance, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Turning Whisper into Real-Time Transcription System, 2023, arXiv (Cornell University)

Frequent co-authors who have collaborated with Ondrej Bojar include:

  • Peter Polák
  • Martin Popel
  • Dominik Macháček
  • Vilém Zouhar
  • Sunit Bhattacharya

Ondrej Bojar has a significant presence in the artificial intelligence research community with specialization in natural language processing and machine translation. Their ongoing work contributes to the understanding and development of advanced machine learning systems for language applications, including translation and speech technologies.

Best Publications

  • Moses: Open Source Toolkit for Statistical Machine Translation

    Philipp Koehn;Hieu Hoang;Alexandra Birch;Chris Callison-Burch

  • 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 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

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

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

  • Training Tips for the Transformer Model

    Unknown

  • Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals.

    Martin Popel;Marketa Tomkova;Jakub Tomek;Łukasz Kaiser

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

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

  • Results of the WMT17 Metrics Shared Task

    Unknown

  • Results of the WMT19 metrics shared task: segment-level and strong MT systems pose big challenges

    Qingsong Ma;Johnny Tian-Zheng Wei;Ondrej Bojar;Yvette Graham

  • Findings of the IWSLT 2022 Evaluation Campaign

    Unknown

  • Results of the WMT14 Metrics Shared Task

    Matous Machacek;Ondrej Bojar

  • Overview of the 1st Workshop on Asian Translation

    Toshiaki Nakazawa;Shohei Higashiyama;Chenchen Ding;Hideya Mino

  • HindEnCorp - Hindi-English and Hindi-only Corpus for Machine Translation

    Ondrej Bojar;Vojtėch Diatka;Pavel Rychl'y;Pavel Stranak

  • Curriculum Learning and Minibatch Bucketing in Neural Machine Translation.

    Tom Kocmi;Ondrej Bojar

  • Results of the WMT16 Metrics Shared Task

    Unknown

  • FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN

    Ebrahim Ansari;Amittai Axelrod;Nguyen Bach;Ondrej Bojar

  • Overview of the 6th Workshop on Asian Translation

    Toshiaki Nakazawa;Nobushige Doi;Shohei Higashiyama;Chenchen Ding

  • Results of the WMT15 Metrics Shared Task

    Miloš Stanojević;Amir Kamran;Philipp Koehn;Ondřej Bojar

  • Results of the WMT20 Metrics Shared Task.

    Nitika Mathur;Johnny Wei;Markus Freitag;Qingsong Ma

  • FINDINGS OF THE IWSLT 2021 EVALUATION CAMPAIGN

    Antonios Anastasopoulos;Ondrej Bojar;Jacob Bremerman;Roldano Cattoni

  • Open Source Toolkit for Statistical Machine Translation: Factored Translation Models and Lattice Decoding

    Philipp Koehn;Marcello Federico;Wade Shen;Nicola Bertoldi

Frequent Co-Authors

Barry Haddow
Barry Haddow University of Edinburgh
Philipp Koehn
Philipp Koehn Johns Hopkins University
Lucia Specia
Lucia Specia Imperial College London
Alex Waibel
Alex Waibel Carnegie Mellon University
Marcello Federico
Marcello Federico Amazon (United States)
Rico Sennrich
Rico Sennrich University of Zurich
Jan Niehues
Jan Niehues Karlsruhe Institute of Technology
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Christof Monz
Christof Monz University of Amsterdam
Chris Dyer
Chris Dyer Google (United States)

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