Twelve PhD theses defended in 2017 were received as candidates for the
2018 edition of the EAMT Best Thesis Award, and all twelve were
eligible. A panel of 41 reviewers was recruited to examine and score the
theses, considering how challenging the problem tackled in each thesis
was, how relevant the results are for machine translation as a field,
and what the strength of its impact in terms of scientific publications
was. It became very clear that 2017 was 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 three EAMT
Executive Committee members (Barry Haddow, Juan Antonio Pérez-Ortiz, and
Mikel L. Forcada) was assembled to process the reviews and select a winner.
The panel has decided to grant the 2018 edition of the EAMT Best Thesis
Award to Daniel Emilio Beck's thesis "Gaussian Processes for Text
Regression" (University of Sheffield, supervised by Lucia Specia).
The awardee will receive a prize of €500, together with a
suitably-inscribed certificate. In addition, Dr. Beck has been invited
to present a summary of his thesis at the Annual Conference of the EAMT
(http://eamt2018.dlsi.ua.es) which will take place in Alacant, May
28–30, 2018. In order to facilitate this, the EAMT will waive the
winner's registration costs, and will make available a travel bursary of
€200.
Mikel L. Forcada
EAMT president
--
Mikel L. Forcada (http://www.dlsi.ua.es/~mlf/)
Departament de Llenguatges i Sistemes Informàtics
Universitat d'Alacant
E-03071 Alacant, Spain
Phone: +34 96 590 9776
Fax: +34 96 590 9326
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