Six PhD theses defended in 2024 were received as candidates for the 2024 edition of the EAMT Best Thesis Award, and all nine were eligible. 13 reviewers 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 2024 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 (Barry Haddow and Rachel Bawden) 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 winner of the 2024 edition of the EAMT Best Thesis Award is Ricardo Rei’s thesis “Robust, Interpretable and Efficient MT Evaluation with Fine-tuned Metrics” (Unbabel, Portugal), supervised by Dr Maria Luísa Torres Ribeiro Marques da Silva Coheur and Dr.  Alon Lavie.

In addition, the committee judged  that the following thesis, was “highly commended”:

• Sara Papi: “Direct Speech Translation in Constrained Contexts: the Simultaneous and Subtitling Scenarios” (FBK, Italy), supervised by Dr. Marco Turchi and Dr. Matteo Negri

The awardee will receive a prize of €500, together with a suitably-inscribed certificate. In addition, Dr. Rei will present a summary of their thesis at the 20th Machine Translation Summit (Mt Summit 2025: https://mtsummit2025.unige.ch/) which will take place from June 23th to 27th in Geneva, Switzerland.  In order to facilitate this, the EAMT will waive the winner’s registration costs, and will make available a travel bursary of €200.

Barry Haddow, chair, EAMT BTA award 2024

Rachel Bawden, chair, EAMT BTA award 2024

Program committee

Marine Carpuat, University of Maryland

Miquel Esplà-Gomis, Universidad de Alicante

Mikel Forcada, Prompsit

Philipp Koehn, Johns Hopkins University

Mary Nurminen, Tampere University

Matt Post, Microsoft

Danielle Saunders, DeepL

Carolina Scarton, University of Sheffield

Rico Sennrich, University of Zurich

Sara Szoc, Crosslang

Jörg Tiedemann, University of Helsinki

François Yvon, CNRS

Marcely Zanon-Boito, Naver Labs