Chris Manning to Give Public Lecture on Deep Learning and Artificial Intelligence at Institute for Advanced Study

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Christopher Manning, Thomas M. Siebel Professor in Machine Learning, Linguistics, and Computer Science at Stanford University, will a give a public lecture, “Deep Learning and Cognition, on Wednesday, November 15, which will take place at 5:00 p.m. in Wolfensohn Hall on the Institute campus. This lecture is part of the Theoretical Machine Learning Lecture Series, a new series curated by Sanjeev Arora, Visiting Professor in the School of Mathematics, and is made possible by a gift from Eric and Wendy Schmidt.

Deep learning, which is the reemergence of artificial neural networks, has recently succeeded as an approach towards artificial intelligence. In many fields, including computational linguistics, deep learning approaches have largely displaced earlier machine learning approaches, due to the superior performance they provide. In this public lecture, Manning will discuss some of the results in computer vision, speech, and language which support the preceding claims. Manning will also explore bigger questions including why and how deep learning methods manage to be so successful, what new perspectives they suggest about human cognition and the language of thought, and what opportunities exist for deep learning to move beyond its core successes on sensory perception and classification tasks to be a broader tool for artificial intelligence.

Manning’s work explores software that can intelligently process, understand, and generate human language material. 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 also focuses on computational linguistic approaches to parsing, robust textual inference, and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies.

Manning earned his Ph.D. in linguistics from Stanford University in 1994. Prior to joining Stanford University as Faculty member in 1999, Manning held positions at Carnegie Mellon University and the University of Sydney. He is a fellow of many professional organizations including the Association for Computing Machinery, the Association for the Advancement of Artificial Intelligence, and the Association for Computational Linguistics, of which he is also a former President (2015). He has coauthored leading textbooks on statistical natural language processing and information retrieval. Manning is also a member of the Stanford Natural Language Processing group and manages development of the Stanford CoreNLP software.

This event is free and open to the public, but registration is required. To register for this event, visit For more information on other public lectures and events at the Institute, visit