New! July 2022: I am an assistant professor of computer science at the University of Richmond!
am was a Research Staff Member at IBM Research, focusing on machine learning and natural language processing (NLP).
I earned my PhD at the University of Michigan, where I studied NLP as part of the CLAIR group, supervised by Dragomir Radev.
I received my bachelor's degree from Boston College and my juris doctorate from the University of Virginia School of Law. I practiced law for several years. My favorite part of my job was trying to understand the technology involved in patent cases I litigated. My least favorite part was document review: reading thousands of documents to figure out which were relevant to a case and to pick out the few needles of useful information in a massive haystack of emails and corporate documents. When I saw IBM's Watson on Jeopardy in 2011, I could not help but be fascinated, both by the potential application of taking over the tedious parts of my job and by the apparent ability of a machine to understand language. In 2013, I left my job as a litigator to study NLP full time.
I am interested in semantics: What information is in a text, how can we represent it, and what can we do with that representation? Like the rest of the NLP community, I am quite interested in how deep learning can be applied to the problems I work on.
I am also curious about what NLP can learn from related fields such as psychology and neurology. What do experts in those areas know about how the human brain represents meaning, and to what extent can that inform our models? As both AI and related fields grow and evolve, I think it is important to regularly come back to this question, as the answers may change.
While at UMich, I was a Graduate Student Instructor (GSI) for the following courses: