Christopher Manning

2024 IEEE John von Neumann Medal Recipient and Panelist for Panel on AI

Christopher Manning is the inaugural Thomas M. Siebel Professor in Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). His research goal is computers that can intelligently process, understand, and generate human languages. Manning is best-known as a leader in applying Deep Learning to Natural Language Processing (NLP), with well-known early research on the GloVe model of word vectors, attention, self-supervised model pre-training, tree-recursive neural networks, and machine reasoning. Earlier on he worked on probabilistic NLP models for parsing, sequence tagging, and grammar induction and he also focuses on computational linguistic approaches to natural language inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning manages development of the open-source Stanford CoreNLP and Stanza software, and his software and algorithms are used in the systems of many companies for tasks such as sentiment analysis, machine translation, dependency parsing, summarization, and question answering. Manning has coauthored leading textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), as well as linguistic monographs on ergativity and complex predicates. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). His research has won ACL, Coling, EMNLP, and CHI Best Paper Awards and an ACL Test of Time award. He has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023, and he held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford, where he founded the Stanford NLP group (@stanfordnlp).