Nine PhD theses defended in 2022 were received as candidates for the 2022 edition of the EAMT Best Thesis Award, and all nine were eligible. 28 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. It became very clear that 2022 was another very good year for PhD theses in machine translation.
All theses had merit, all candidates had strong CVs and, therefore, it was very difficult to select a winner.
A panel of two EAMT Executive Committee members (Carolina Scarton and Helena Moniz) was assembled to process the reviews and select a winner that was later ratified by the EAMT executive committee.
We are pleased to announce that the awardee of the 2022 edition of the EAMT Best Thesis is Biao Zhang’s thesis “Towards Efficient Universal Neural Machine Translation” (University of Edinburgh, UK), supervised by Dr Rico Sennrich and Dr Ivan Titov.
The awardee will receive a prize of €500, together with a suitably-inscribed certificate. In addition, Dr. Zhang will present a summary of their thesis at the 24th Annual Conference of the European Association for Machine Translation (EAMT 2023: https://events.tuni.fi/eamt23/) which will take place from June 12th to 15th in Tampere, Finland. In order to facilitate this, the EAMT will waive the winner’s registration costs, and will make available a travel bursary of €200.
Helena Moniz, EAMT President
Carolina Scarton, EAMT Secretary
Rachel Bawden, Inria
Daniel Beck, The University of Melbourne
William Byrne, University of Cambridge
José G. C. de Souza, Unbabel
Vera Cabarrão, Unbabel / INESC-ID
Sheila Castilho, Dublin City University
Anna Currey, Amazon Web Services
Mattia Antonino Di Gangi, AppTek
Maha Elbayad, LIG/ Inria
Miquel Esplà-Gomis, Universitat d’Alacant
Marcello Federico, Amazon AI
Mikel Forcada, DLSI – Universitat d’Alacant
Barry Haddow, The University of Edinburgh
Diptesh Kanojia, IIT Bombay
Philipp Koehn, Johns Hopkins University
Helena Moniz, INESC/FLUL
Mary Nurminen, Tampere University
Constantin Orasan, University of Surrey
John E. Ortega, Northeastern University
Santanu Pal, Wipro Limited
Pavel Pecina, Charles University
Maja Popovic, ADAPT Centre @ DCU
Celia Rico, Universidad Complutense de Madrid
Víctor M. Sánchez-Cartagena, Universitat d’Alacant
Marina Sánchez-Torrón, Unbabel
Danielle Saunders, University of Cambridge
Dimitar Shterionov, Tilburg University
Felix Stahlberg, Google Research
Arda Tezcan, Ghent University
Antonio Toral, University of Groningen
Ualsher Tukeyev, al-Farabi Kazakh National University
Bram Vanroy, KU Leuven; Ghent University
Longyue Wang, Tencent AI Lab