CNRS Research Director, Head of the CNRS Lattice research unit (2012-2018) and adjunct head since 2019. Affiliated lecturer, Language Technology Laboratory, U. of Cambridge since 2009. Rutherford fellowship, Turing institute, London, 2018-2019. Teaching NLP in the PSL Master in Digital Humanities.
Topics of interest
Computational linguistics, Low resource languages, Corpora, Distant reading, AI and creativity
Project in Prairie
Thierry Poibeau’s work focuses on Natural Language Processing. He is especially interested in developing techniques for low resource languages that have largely been left out of the machine learning revolution. He is also interested in applying AI techniques to the study of literature and social sciences, shedding new light on the notions of culture and creativity.
Natural Language Processing (NLP) has made considerable progress over the last few years, mainly due to impressive advances in machine learning. We have now efficient and accurate tools for 20+ languages, but the vast majority of the world languages lack the resources for state-of-the-art NLP. This is a major challenge for our field, since preserving language and cultural diversity is as important as preserving bio-diversity. Technology is not the only solution, but it helps facilitate this process by leveraging resources, bridging the gap between languages, and enhancing our understanding of culture and society.