Christopher Manning
Thomas M. Siebel Professor in Machine Learning at Stanford University
A Stanford professor of linguistics and computer science whose work on GloVe, attention and open-source NLP tools shaped language AI.
Biography
Christopher Manning is an Australian-American computer scientist and applied linguist, and the inaugural Thomas M. Siebel Professor in Machine Learning at Stanford University, where he is a professor of linguistics and computer science. He earned a BA with honours in mathematics, computer science and linguistics from the Australian National University in 1989 and a PhD in linguistics from Stanford in 1994.
He is known for co-developing GloVe word vectors, the bilinear or multiplicative form of attention now widely used in neural networks including the transformer, and tree-structured recursive neural networks. He directed the Stanford Artificial Intelligence Laboratory from 2018 to 2025 and wrote the textbooks Foundations of Statistical Natural Language Processing and Introduction to Information Retrieval. Since 2002 he has also driven open-source software such as CoreNLP and Stanza, and he is namesake of Manning's Law in Universal Dependencies. His former PhD students include Dan Klein, Richard Socher and Danqi Chen.
Notable contributions
Co-developed GloVe word vectors
With Jeffrey Pennington and Richard Socher, developed GloVe, an unsupervised method for learning word embeddings from corpus statistics.
Co-developed multiplicative attention
Co-developed the bilinear or multiplicative form of attention, now widely used in neural networks including the transformer.
Directed the Stanford AI Laboratory
Served as director of the Stanford Artificial Intelligence Laboratory from 2018 to 2025.