Tom McCoy, PhD

Tom McCoy's research uses computational modeling to study how humans learn and represent language. On the side of learning, he investigates how people can acquire language from so little data and how we can replicate this ability in machines. On the side of representations, he investigates what types of machines can represent the structure of language and how they do it. Much of his research involves large language models, with an emphasis on connecting such systems to linguistics. This work combines computational linguistics, cognitive science, and artificial intelligence.

computational modeling ;  deep learning ;  neural networks  

artificial intelligence ;  cognition ;  language ;  learning ;  machine learning ;  natural language processing  

Tom McCoy received a BA in Linguistics from Yale in 2017 and a PhD in Cognitive Science from Johns Hopkins in 2022. He was a postdoc in Computer Science at Princeton before joining Yale as a faculty member in 2024. His hobbies include long-distance running and crossword puzzle construction.