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Visiting Assistant Professor of Computer Science
"Context in natural language is rooted in an understanding of intention and convention. The task of unravelling sentential meaning can be approximated by an application of static lexical knowledge of syntax and semantics to the contextual in order to create a graphical representation. My current research focuses on applying word sense information to the task of Semantic Parsing.
"In particular, my research applies heuristic measures from high level statistical systems in order to guide the handcrafted TRIPS semantic parser. The intuitive difference between word senses such as a bank as a "financial institution" and bank as the "land by a body of water" can be vital in avoiding errors in the final logical conclusions drawn by automated natural language understanding systems.
"In my spare time, I enjoy reading, cooking, listening/making noise, and petting cats."
Years at Knox: 2020 to present
Ph.D., Computer Science, University of Rochester
M.Sc., Computer Science, Stony Brook University
B.A., Computer Science and Mathematics, Colgate University
Natural language processing, semantic parsing.
“A Broad-Coverage Deep Semantic Lexicon for Verbs,” Language Resources and Evaluation, 2020
“SkeletonScore: Guiding a Semantic Parser to Better Results by Example”, The Thirty-First International Flairs Conference, 2018
“The kissing problem: how to end a gathering when everyone kisses everyone else goodbye.” Theory of Computing Systems. Springer US, 2013.
"The kissing problem: how to end a gathering when everyone kisses everyone else goodbye." Fun with Algorithms. Springer Berlin Heidelberg, 2012.
"Learning general connotation of words using graph-based algorithms." Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2011.
“Student Abstract: Improving Semantic Parsing using Statistical Word Sense Disambiguation”, Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020.