My research focuses on the computational foundations of intelligent behavior. We develop theories and systems pertaining to intelligent behavior using a unified methodology -- at the heart of which is the idea that learning has a central role in intelligence.
My work centers around the study of machine learning and inference methods to facilitate
natural language understanding. In doing that I have pursued several interrelated lines of work that span multiple aspects of this problem - from fundamental questions in
learning and inference and how they interact, to the study of a range of natural language processing (NLP) problems including shallow parsing, semantic role labeling, co-reference, question answering and textual entailment, to fundamental problems in Language Acquisition, ESL, and Information Trustworthiness. We are also engaged in large scale Natural Language Processing and Information Extraction system development, from basic NLP tools to Wikification, resulting in a number of software packages for NLP tools and Demos that are available from my web site and are widely used by the community.