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Christopher Manning

Natural Language Processing (NLP) Neural Machine Translation Self-Supervised Model Pre-Training Dependency Parsing Tree-Recursive Neural Networks
Stanford University Computer Science

About

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). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing, work for which he won ACL, Coling, EMNLP, and CHI Best Paper Awards. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. In linguistics, Manning is a principal developer of Stanford Dependencies and Universal Dependencies, and has authored monographs on ergativity and complex predicates. He is the founder of the Stanford NLP group (@stanfordnlp) and was an early proponent of open source software in NLP with Stanford CoreNLP and Stanza. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning 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. He held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford.

Research Performance Summary

605
Total Papers
340144
Total Citations
176
H-Index
1991-2025
Active Research Span

First Recorded Paper

Lexical Conceptual Structure and Marathi

Year: 1991

Citations: 1

Venue: Ms., Stanford University

Latest Recorded Paper

Universal Dependencies for Sindhi

Year: 2025

Citations: 0

Venue: Proceedings of the Eighth Workshop on Universal Dependencies (UDW

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2025
26
2024
26
2023
21
2022
20
2021
22
2020
18
2019
11
2018
11
2017
18
2016
15
2015
32

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 270
Journal 16
Book 46

Top Coauthors

Manning Schütze

Research Impact by Period

2025-2026

Period Stats
Papers 26
Citations 650
Avg. Citations / Paper 25
H-Index 8

2020-2024

Period Stats
Papers 107
Citations 42442
Avg. Citations / Paper 396.7
H-Index 49

2015-2019

Period Stats
Papers 87
Citations 62297
Avg. Citations / Paper 716.1
H-Index 53

2010-2014

Period Stats
Papers 154
Citations 108576
Avg. Citations / Paper 705
H-Index 69

2005-2009

Period Stats
Papers 110
Citations 83667
Avg. Citations / Paper 760.6
H-Index 57

2000-2004

Period Stats
Papers 70
Citations 20696
Avg. Citations / Paper 295.7
H-Index 41

1995-1999

Period Stats
Papers 42
Citations 20685
Avg. Citations / Paper 492.5
H-Index 17

1990-1994

Period Stats
Papers 9
Citations 1131
Avg. Citations / Paper 125.7
H-Index 5

Contact and Professional Links

Contact Information

manning@stanford.edu
6507237683

Detected Research Keywords

Natural Language Processing Named Entity Recognition Natural Language Inference Introduction Information Retrieval Recursive Neural Networks Statistical Machine Translation Foundations Statistical Natural Statistical Natural Language Neural Machine Translation Semantic Role Labeling