My interests include natural language processing and applying machine learning to various real world problems (automatic translation, healthcare, computational advertising etc). My thesis research was in the realm of question answering. In the past few years I have worked on applied machine learning and data mining, particularly on natural language problems such as question answering, automatic content extraction, detecting semantic coherence, case restoration, machine translation and automatic MT evaluation, as well as multi-agent planning under uncertainty (with Sebastian Thrun). My Ph.D. advisor was Jaime Carbonell.
My Ph.D. thesis focus was "Instance
Based Question Answering", a statistical,
data-driven approach to question answering in which we
learn multiple answering strategies directly from training
questions and answers. Thesis committee: Jaime Carbonell (CMU), Eric Nyberg (CMU), Tom Mitchell (CMU),
Nanda Kambhatla (IBM TJ Watson)