Thomas Moerman PhD Researcher in NLP and AI, Ghent University (LT3)
I develop retrieval-augmented and synthetic-data methods for natural language processing (NLP) and artificial intelligence (AI), applied to a range of tasks such as machine translation, educational NLP, and fairness in language models.
News
- October 2026 Research stay at Transducens, Universitat d’Alacant, opened with a kickoff talk, Fuzzy Matches and Synthetic Data for Machine Translation.
- October 2026 Presented ContraGAND, a contrastive corpus for gender ambiguity detection, as a poster at EMNLP 2026 in Budapest. The paper is in the ACL Anthology, with the dataset, models and a demo on Hugging Face.
- October 2026 Our WMT 2026 submission for multitask Sorbian NLP was the joint winner of the Sorbian track at the Conference on Machine Translation (WMT).
- September 2026 At CLIN 36 in Brussels, gave an oral presentation, Synthetic Data for Machine Translation, and presented the SanreMello Corpus poster, seven decades of Sanremo and Melodifestivalen as data.
- August 2026 Our EAMT 2026 paper on machine translation in the asylum context is now published in the ACL Anthology.
- July 2026 Taught the five-day Introduction to Python module at the MILS summer school (Methods in Language Sciences), Ghent University.
- June 2026 Presented our EAMT 2026 paper on machine translation in the asylum context, shortlisted for a best-paper award.
- May 2026 ShAnEL-2, our multilingual short-answer grading dataset, was accepted at LREC 2026.