Abstract
Data science holds the promise to solve many of society’s most pressing challenges. But much of the necessary data is locked within the volumes of text and speech on the web. Thus, in many cases, data science can only succeed if paired with natural language processing. In this talk, the speaker will describe research projects that draw from language data along a continuum from fact to fiction. She will present a system that predicts the future impact of a scientific concept—represented as a technical term—based on the information available in recently published research articles, research on learning from knowledge of past disasters, as seen through the lens of the media and on the use of data science in a far different discipline, the field of literature.
About the speaker
Prof Kathleen McKeown received her PhD in Computer Science from the University of Pennsylvania in 1982. She joined Columbia University after that and has been faculty there since then. She served as Department Chair from 1998 to 2003 and as Vice Dean for Research for the School of Engineering and Applied Science for two years. She is currently the Henry and Gertrude Rothschild Professor of Computer Science and the Director of the Institute for Data Sciences and Engineering at Columbia.
Prof McKeown’s research interests include text summarization, natural language generation, multi-media explanation, question-answering and multi-lingual applications.
Prof McKeown received numerous awards including the National Science Foundation Presidential Young Investigator Award, the National Science Foundation Faculty Award for Women, the Anita Borg Institute Women of Vision Award in Innovation and the Instructional Technology Research Award, etc. She is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery, and a founding Fellow of the Association for Computational Linguistics.
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