EAMT best thesis award

2019 EAMT Best Thesis Awardee

Ten PhD theses defended in 2019 were received as candidates for the 2019 edition of the Anthony C Clarke Award – EAMT Best Thesis Award, and all ten were eligible. 36 reviewers and six EAMT Executive Committee members were recruited to examine and score the theses, considering how challenging the problem tackled in each thesis was, how relevant the results were for machine translation as a field, and what the strength of its impact in terms of scientific publications was. Two EAMT Executive Committee members also analysed all theses.

The year of 2019 was again a very good year for PhD theses in machine translation. The scores of the best theses were very close, which made it very hard to select a winner. A panel of five EAMT Executive Committee members (André Martins, Lucia Specia, Khalil Sima’an, Carolina Scarton, and Mikel L. Forcada) was assembled to process the reviews and select a winner.

The panel has then decided to grant the 2019 edition of the EAMT Best Thesis Award to Felix Stahlberg’s thesis “The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction” (University of Cambridge — now at Google), supervised by Bill Byrne and with Phil Woodland as advisor.

The awardee will receive a prize of €500, together with a suitably-inscribed certificate. In addition, Dr. Stahlberg has been invited to present a summary of his thesis at the 22nd Annual Conference of the European Association for Machine Translation (EAMT 2020: https://eamt2020.inesc-id.pt) which will take place in November (dates to be confirmed).

Mikel L. Forcada

EAMT President

Carolina Scarton

EAMT Secretary

Program committee

We would like to thank our reviewers that, despite the COVID-19 pandemic, still gave their time to review the theses and help us select the winner. Specially, Julia Ive, Iacer Calixto, José G. C. de Souza, and Jesús González Rubio that also acted as emergency reviewers.

  • Alon Lavie, Carnegie Mellon University
  • Andreas Maletti, Universität Leipzig
  • André Martins, Unbabel
  • Andy Way, Dublin City University
  • Antonio Toral, University of Groningen
  • Barry Haddow, University of Edinburgh
  • Celia Rico, Universidad Europea de Madrid
  • Christian Hardmeier, Uppsala University
  • Cristina España-Bonet, UdS and DFKI
  • Daniel Beck, University of Melbourne
  • Dimitar Shterionov, Dublin City University
  • Ekaterina Lapshinova-Koltunsk, Saarland University
  • Federico Gaspari, Dublin City University
  • Francisco Casacuberta, Universitat Politècnica de València
  • François Yvon, Université Paris-Sud
  • Frederic Blain, University of Sheffield
  • Iacer Calixto, University of Amsterdam
  • Jan Niehues, Maastricht University
  • Jesús González Rubio, WebInterpret
  • Joke Daems, Ghent University
  • José G. C. de Souza, Unbabel
  • Julia Ive, Imperial College London
  • Lieve Macken, Ghent University
  • Loïc Barrault, University of Sheffield
  • Longyue Wang, Tencent AI Lab
  • Lucia Specia, Imperial College London
  • Maja Popovic, Dublin City University
  • Marcello Federico, Amazon AI
  • Markus Freitag, Google AI
  • Matteo Negri, Fondazione Bruno Kessler
  • Mauro Cettolo, Fondazione Bruno Kessler
  • Miguel Domingo, Universitat Politècnica de València
  • Miquel Esplà, Universitat d’Alacant
  • Patrick Simianer, Lilt Inc.
  • Pavel Pecina, Charles University
  • Philipp Koehn, Johns Hopkins University
  • Qun Liu, Huawei Noah’s Ark Lab
  • Rico Sennrich, University of Zurich
  • Sharon O’Brien, Dublin City University
  • Sheila Castilho, Dublin City University
  • Vincent Vandeghinste, KU Leuven
EAMT best thesis award

The Anthony C. Clarke Award for the 2019 EAMT Best Thesis

The European Association for Machine Translation (EAMT, http://www.eamt.org) is an organization that serves the growing community of people interested in MT and translation tools, including users, developers, and researchers of this increasingly viable technology.

The EAMT invites entries for eighth EAMT Best Thesis Award for a PhD or equivalent thesis on a topic related to machine translation.


Researchers who

  • have completed a PhD (or equivalent) thesis on a relevant topic in a European, Northern African[1] or Middle Eastern[2] institution within calendar year 2019 and
  • have not previously won another international award for that thesis,


The submissions will be judged by a panel of experts who will be specifically appointed as part of the EAMT 2020 programme committee and which will be ratified by the Executive Board of the EAMT.

Selection criteria

Each thesis will be judged according to how challenging the problem was, to how relevant the results are for machine translation as a field, and to the strength of their impact in terms of scientific publications.


The scope of the thesis need not be confined to a technical area, and applications are also invited from students who carried out their research into commercial and management aspects of machine translation.

Possible areas of research include:

  • development of machine translation or advanced computer-assisted translation: methods, software or resources
  • machine translation for less-resourced languages
  • the use of these systems in professional environments (freelance translators, translation agencies, localisation, etc.)
  • the increasing impact of machine translation on non-professional Internet users and its impact in communications, social networking, etc.
  • spoken language translation
  • the integration of machine translation and translation memory systems
  • the integration of machine translation software in larger IT applications
  • the evaluation of machine translation systems in real tasks such as those above
  • the cross-fertilisation between machine translation and other language technologies


The winner will be announced at the same time as accepted papers for the EAMT 2020: the 22nd Annual Conference of the European Association for Machine Translation (Lisbon, Portugal, dates to be confirmed), and will receive a prize of €500, together with an inscribed certificate. The recipient of the award will be required to briefly present their research at EAMT 2020. In order to facilitate this, the EAMT will waive the winner’s registration costs, and will make available a travel bursary of €200 to enable the recipient of the award to attend the said conference. The prize includes complimentary membership in the EAMT for 2020 and 2021.


Candidates will submit using EasyChair: https://easychair.org/conferences/?conf=eamt2020 (Submission type: Thesis Award), a single PDF file containing, in this order:

  • a 2-page summary of your thesis in English, containing:
    • your full contact details,
    • the name and contact details of your supervisor(s),
  • a copy of your CV in English (at most one page, plus a complete list of publications directly related to the thesis)
  • an electronic copy of your thesis
  • optionally, an appendix with any other relevant information on the thesis

By submitting their work, authors

  • agree that, in case they are granted the award, any subsequently published version of the thesis should carry the citation “The Anthony C. Clarke Award for the 2019 EAMT Best Thesis” and
  • acknowledge the right of the EAMT to publicize the granting of the award.

Closing date

The closing date for submissions will be the same as the deadline for EAMT 2020 research papers: TBA.

[1] Algeria, Egypt, Libya, Morocco and Tunisia.
[2] Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Oman, Palestine, Qatar, Saudi Arabia, Syria, United Arab Emirates, Yemen.