Tom McCoy is a computational linguist who studies how language is learned and represented in humans and artificial neural networks. He received his PhD in Cognitive Science from Johns Hopkins University in 2022, after which he was a postdoctoral fellow at Princeton University in the Department of Computer Science from 2022 to 2023. Since January 2024, he has been an Assistant Professor of Linguistics at Yale University.

The broad goal of his research is to identify the computational mechanisms that underlie the human language faculty. More concretely, his work focuses on two main directions: (i) Understanding how the sophisticated syntactic structure prevalent in linguistic theory can be represented in the vector representations of neural networks - systems that, despite appearing poorly suited for processing language, are the state of the art in artificial intelligence. (ii) Using computational modeling and human experiments to analyze which learning mechanisms account for our incredible ability to acquire language at such a young age and from so little data. Through these research directions, he aims to bridge the divide between linguistics and artificial intelligence (AI): How can the scientific study of language be informed by advances in AI, and how can AI systems be improved by insights from linguistics? Outside of research, he is an organizer of the North American Computational Linguistics Open competition (NACLO), a competition that introduces high school students to linguistics.