Roy’s lab studies Natural Language Processing (NLP). Our research is driven towards making text NLP widely accessible—to doctors, to teachers, to researchers or even to curious teenagers. To be broadly adopted, NLP technology needs to not only be accurate, but also reliable; models should provide explanations for their outputs; and the methods we use to evaluate them need to be convincing.
We also study methods to make NLP more efficient and green, in order to decrease the environmental impact of the field, as well as lower the cost of AI research in order to broaden participation in it.
Journal cover; Communications of the ACM (CACM)
Best paper award; Workshop on Representation Learning for NLP (RepL4NLP)
Israeli Science Foundation (ISF) Grant
U.S.-Israeli Binational Science Foundation (NSF-BSF) Grant
Intel Research Gift
Google Research Gift
Allen Institute for AI Research Gift