Bonnie Dorr

Florida Institute for Human and Machine Cognition

Lecture Information:
  • December 1, 2017
  • 2:00 PM
  • ECS 241
Photo of Bonnie J. Dorr

Speaker Bio

Bonnie Dorr is a Senior Research Scientist and Associate Director of IHMC Ocala, Florida, as well as Professor Emeritus of Computer Science at the University of Maryland and Professor of Computer Science at the University of Florida (courtesy).  She is a former DARPA Program Manager of Human Language Technology, and served as Maryland’s Associate Dean for the College of Computer, Mathematical, and Natural Sciences (CMNS).  She co-founded the Computational Linguistics and Information Processing (CLIP) Laboratory in the Institute for Advanced Computer Studies at the University of Maryland. She was also Principal Scientist for two years at the Johns Hopkins University Human Language Technology Center of Excellence (HLTCOE).  For 30 years, she has been conducting research in several areas of broad-scale multilingual processing, e.g., machine translation, summarization, and deep language understanding.  She is an associate editor of ACM Computing Surveys, a Sloan Fellow, a NSF Presidential Faculty (PECASE) Fellow, an elected Fellow of the Association for Advancement of Artificial Intelligence, a Fellow (and former President) of the Association for Computational Linguistics, and an inducted member of the Leadership Florida Class of XXXIII.


Natural language researchers and data scientists apply a multitude of techniques for analysis and extraction of knowledge from potentially massive data. For example, natural language processing of unstructured data enables the discovery of possible cyber threats. Extraction of goals and intentions may lead to predictions of when an event may occur in cyberspace. This talk describes IHMC research on predictive analytics applied to formal and informal textual data and includes a cross-field examination of problems, measures, and evaluation paradigms designed to support solutions to data-science problems that span a wide range of fields.