Tom McCoy is an Assistant Professor of Linguistics at Yale University, with a secondary appointment in Computer Science. His research aims to bridge the divide between neural networks, probabilistic models, and symbolic systems: how can we build cognitive theories that combine the complementary strengths of these traditions? He focuses on the domain of language, investigating the representations and inductive biases that underlie human language learning and processing. Much of this work makes contact with neural network language models from artificial intelligence, with the goal of characterizing what these systems have learned and how they operate. He received his PhD from the Department of Cognitive Science at Johns Hopkins, and his PhD thesis received a Glushko Dissertation Prize from the Cognitive Science Society and the Glushko-Samuelson Foundation. He then did a postdoc in Computer Science at Princeton before joining the faculty at Yale. Outside of research, he is an organizer and problem writer for NACLO, a contest that introduces high school students to linguistics and natural language processing.