My research falls under the heading of Natural Language Processing which is itself a sub-discipline of Artificial Intelligence (AI). In my research, I develop algorithms that try to "understand" text in the same ways that you (presumably a human) understand text. My interest in natural language comes from an appreciation of the brain's ability to effortlessly produce and understand written and spoken language. We take for granted our ability to read a newspaper or recommend a book to a friend. However, these mundane tasks belie the brain's incredible capacity for storing, processing, and generalizing information.

Currently, I'm working on a few different projects: dialogue systems in open-domain conversational agents and semantic representations (i.e. how to capture the meaning while minimizing other counfounding factors such as word choice). The techniques that I use in my research come from various sub-disciplines of AI including graphical models, statistical pattern recognition, gradient-based optimization, supervised learning, and natural language processing. Many of these techniques are grounded in probability and statistics.