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Marco Valenzuela-Escárcega


Research Scientist, Computer Science, University of Arizona

Marco's research is in Natural Language Processing and Information Extraction. He is the primary author of the Odin rule language and runtime system, as well as its highly optimized successor, Odinson. These tools have been used to build large-scale information extraction systems over several domains including biomedical, public health, agriculture, astronomy, and social science, among others. He is currently interested in methods for assisting domain-experts to better use these tools to build their own information extraction systems without requiring them to have knowledge of linguistics or NLP.

Rebecca Sharp


Assistant Research Professor, Linguistics, University of Arizona

Rebecca’s research is in Linguistics and Natural Language Processing, where she uses a variety of rule-based and machine learning approaches to extract and assemble knowledge in order to perform and explain approximate inference. Her work is very interdisciplinary and she collaborates actively with researchers in Linguistics, Computer Science, Information, and Nursing. This allows her to work with people from diverse backgrounds and with a wide variety of information needs, skills, approaches, and analysis techniques.

Gus Hahn-Powell


Assistant Professor, Linguistics, University of Arizona

Gus is a core contributor to numerous information extraction and knowledge assembly systems which hybridize linguistic rules and statistical methods. His research interests center around machine reading for scientific discovery and in building systems to scour the literature, analyze findings, and synthesize discoveries to generate novel hypotheses.

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This material is based upon work supported by the National Science Foundation under Grant No. 2006583 Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.