My research aims to understand the computational principles underlying human language and communication. What representations and algorithms support language learning, comprehension, and production? How does language interact with other forms of knowledge and reasoning? And how can our understanding of human cognition help us develop better systems of artificial intelligence? My lab approaches these questions by integrating computational modeling, behavioral experiments, and AI. Before joining Johns Hopkins, I worked with Tomer Ullman as a Research Fellow at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University. I completed by PhD in Cognitive Science at MIT, where I was advised by Roger Levy.