Difference between revisions of "User:Nschneid"
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| − | Nathan Schneider is an annotation schemer and computational modeler for natural language. As Assistant Professor of Linguistics and Computer Science at Georgetown University, he looks for synergies between practical language technologies and the scientific study of language. He specializes in broad-coverage semantic analysis: designing linguistic meaning representations, annotating them in corpora, and automating them with statistical natural language processing techniques. A central focus in this research is the nexus between grammar and lexicon as manifested in multiword expressions and adpositions/case markers. He has inhabited UC Berkeley (BA in Computer Science and Linguistics), Carnegie Mellon University (Ph.D. in Language Technologies), and the University of Edinburgh (postdoc). Now a Hoya and leader of NERT, he continues to play with data and algorithms for linguistic meaning. | + | [http://nathan.cl Nathan Schneider] is an annotation schemer and computational modeler for natural language. As Assistant Professor of Linguistics and Computer Science at Georgetown University, he looks for synergies between practical language technologies and the scientific study of language. He specializes in broad-coverage semantic analysis: designing linguistic meaning representations, annotating them in corpora, and automating them with statistical natural language processing techniques. A central focus in this research is the nexus between grammar and lexicon as manifested in multiword expressions and adpositions/case markers. He has inhabited UC Berkeley (BA in Computer Science and Linguistics), Carnegie Mellon University (Ph.D. in Language Technologies), and the University of Edinburgh (postdoc). Now a Hoya and leader of NERT, he continues to play with data and algorithms for linguistic meaning. |
Latest revision as of 14:32, 20 September 2017
Nathan Schneider is an annotation schemer and computational modeler for natural language. As Assistant Professor of Linguistics and Computer Science at Georgetown University, he looks for synergies between practical language technologies and the scientific study of language. He specializes in broad-coverage semantic analysis: designing linguistic meaning representations, annotating them in corpora, and automating them with statistical natural language processing techniques. A central focus in this research is the nexus between grammar and lexicon as manifested in multiword expressions and adpositions/case markers. He has inhabited UC Berkeley (BA in Computer Science and Linguistics), Carnegie Mellon University (Ph.D. in Language Technologies), and the University of Edinburgh (postdoc). Now a Hoya and leader of NERT, he continues to play with data and algorithms for linguistic meaning.