Thomas Moerman is a PhD researcher specializing in retrieval-based Machine Translation. His research at the Language Translation and Technology Team (LT3) focuses on improving machine translation systems by using existing translations.
Before starting his PhD, he was involved in research at the VUB Artificial Intelligence Laboratory, focusing on Fluid Construction Grammar, merging linguistic theory with artificial intelligence.
He holds a Master's degree in Linguistics from Ghent University and an Advanced Master's in Natural Language Processing, a collaborative program between KU Leuven and Ghent University.
Currently, his work contributes to the field of natural language processing, with a particular interest in the mechanics and applications of machine translation.
