Christopher Manning’s research goal is computers that can intelligently process, understand, and generate human language material. Manning concentrates on machine learning approaches to computational linguistic problems, including syntactic parsing, computational semantics and pragmatics, textual inference, and machine translation. He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, sentiment analysis, neural network dependency parsing, the GloVe model of word vectors, neural machine translation and deep language understanding. He was the 2015 President of the Association for Computational Linguistics and he has coauthored leading textbooks on statistical natural language processing and information retrieval. He is a member of the Stanford NLP group (@stanfordnlp).
Fellow, Association for Computing Machinery, 2013.
Fellow, Association for the Advancement of Artificial Intelligence
Fellow, Association for Computational Linguistics, 2011.
C.D. Manning, P. Raghavan and H. Schütze, Introduction to Information Retrieval, Cambridge University Press 2008
C.D. Manning and H. Schütze, Foundations of Statistical Natural Language Processing, The MIT Press 1999
A. Andrews and C.D. Manning, Complex Predicates and Information Spreading in LFG (Center for the Study of Language and Information - Lecture Notes), Center for the Study of Language and Inf 1999
Associate Fellow Learning in Machines & Brains
Stanford UniversityDepartment of Computer Science
Ph.D. Stanford University
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