William Mattingly is a Postdoctoral Fellow at the Smithsonian Institution Data Science Lab in collaboration with the United States Holocaust Memorial Museum (USHMM). He has a B.A. and M.A. in History from Florida Gulf Coast University and a Ph.D. in History from the University of Kentucky. His dissertation research explored using historical social network analysis, cluster analysis, and computational methods for identifying ninth-century intellectual and pedagogical networks. Most recently, his research has focused on developing text classification neural network models to identify sources in medieval texts and developing natural language processing (NLP) methods for medieval Latin. At the Smithsonian and USHMM, he is developing machine learning methods to aid, in among other things, the cataloging of Holocaust documents.
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