Daniel Khashabi is an assistant professor of computer science at Johns Hopkins University and a member of the Center for Language and Speech Processing.
Khashabi’s work focuses on computational foundations of intelligent behavior within various mediums of communication, particularly natural language. This involves developing formalisms that characterize and result in natural language processing systems that are capable of understanding and reasoning with (and about) an uncertain world while being general enough to handle a broader space of contexts.
He obtained a PhD from the University of Pennsylvania in 2019 and a BSc from Amirkabir University of Technology (Tehran Polytechnic) in 2012. Before joining Johns Hopkins, he was a postdoctoral fellow at the Allen Institute for AI (2019-2022).
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Inspired by journalists, Hopkins researchers discover a new technique to ground a large language model’s answers in reality.
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The Annual Meeting of the Association for Computational Linguistics is the top international scientific and professional conference for researchers working in the field of natural language processing and computation.
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The winning proposals will receive up to $75,000 each to help innovate learning through technology.