World's Best Scientists 2026 revealed!
Christopher D. Manning

Christopher D. Manning

Award Badge
Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
155
Citations
217855
World Ranking
25
National Ranking
15

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2013 - ACM Fellow For contributions to natural language processing research and education.
  • 2010 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to statistical natural language processing, including in statistical parsing and grammar induction, and education through leading textbooks.

Overview

Christopher D. Manning is affiliated with Stanford University in the United States. Their work spans numerous areas within computer science, with a particular focus on artificial intelligence and natural language processing. Over the course of their career, they have contributed extensively to these fields through research, publications, and collaboration with other scholars.

The main fields of study for this scientist include:

  • Computer Science

Their subfields of specialization consist of:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Political Science and International Relations
  • Health Informatics

Christopher D. Manning's research topics cover a diverse range of subjects such as:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Adversarial Robustness in Machine Learning
  • Biomedical Text Mining and Ontologies
  • Domain Adaptation and Few-Shot Learning

Some recent papers contributed by Manning include:

  • On the Opportunities and Risks of Foundation Models, 2021, arXiv (Cornell University)
  • Question Answering For Toxicological Information Extraction, 2022, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Universal Dependencies for Multilingual Open Information Extraction, 2021, arXiv (Cornell University)
  • Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models, 2022, arXiv (Cornell University)
  • ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators, 2020, arXiv (Cornell University)

Frequent co-authors who have collaborated with Manning include:

  • Christopher Potts
  • Shikhar Murty
  • Percy Liang
  • Chelsea Finn
  • Eric Mitchell

The primary venues where Manning's work has been published are:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Archives of Orthopaedic and Trauma Surgery
  • Bulletin of Indonesian Economic Studies

Throughout their career, Christopher D. Manning has received the following awards:

  • ACM Fellow (2013) for contributions to natural language processing research and education
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) (2010) for contributions to statistical natural language processing, including statistical parsing and grammar induction, and education through leading textbooks

Best Publications

  • Glove: Global Vectors for Word Representation

    Jeffrey Pennington;Richard Socher;Christopher Manning

  • Introduction to Information Retrieval

    Christopher D. Manning;Prabhakar Raghavan;Hinrich Schütze

  • Foundations of Statistical Natural Language Processing

    Christopher D. Manning;Hinrich Schütze

  • Effective Approaches to Attention-based Neural Machine Translation

    Minh-Thang Luong;Hieu Pham;Christopher D. Manning

  • The Stanford CoreNLP Natural Language Processing Toolkit

    Christopher Manning;Mihai Surdeanu;John Bauer;Jenny Finkel

  • Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

    Richard Socher;Alex Perelygin;Jean Wu;Jason Chuang

  • Feature-rich part-of-speech tagging with a cyclic dependency network

    Kristina Toutanova;Dan Klein;Christopher D. Manning;Yoram Singer

  • Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling

    Jenny Rose Finkel;Trond Grenager;Christopher Manning

  • Accurate Unlexicalized Parsing

    Dan Klein;Christopher D. Manning

  • A large annotated corpus for learning natural language inference

    Samuel R. Bowman;Gabor Angeli;Christopher Potts;Christopher D. Manning

  • Get To The Point: Summarization with Pointer-Generator Networks

    Abigail See;Peter J. Liu;Christopher D. Manning

  • Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

    Kai Sheng Tai;Richard Socher;Christopher D. Manning

  • Generating Typed Dependency Parses from Phrase Structure Parses

    Marie-Catherine de Marneffe;Bill MacCartney;Christopher D. Manning

  • A Fast and Accurate Dependency Parser using Neural Networks

    Danqi Chen;Christopher Manning

  • Reasoning With Neural Tensor Networks for Knowledge Base Completion

    Richard Socher;Danqi Chen;Christopher D Manning;Andrew Ng

  • Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora

    Daniel Ramage;David Hall;Ramesh Nallapati;Christopher D. Manning

  • Parsing Natural Scenes and Natural Language with Recursive Neural Networks

    Richard Socher;Cliff C. Lin;Chris Manning;Andrew Y. Ng

  • Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger

    Kristina Toutanvoa;Christopher D. Manning

  • HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

    Zhilin Yang;Peng Qi;Saizheng Zhang;Yoshua Bengio

  • Foundations of statistical natural language processing

    Gerhard Weikum

Frequent Co-Authors

Dan Jurafsky
Dan Jurafsky Stanford University
Hinrich Schütze
Hinrich Schütze Ludwig-Maximilians-Universität München
Prabhakar Raghavan
Prabhakar Raghavan Google (United States)
Daniel Klein
Daniel Klein University of California, Berkeley
Marie-Catherine de Marneffe
Marie-Catherine de Marneffe The Ohio State University
Andrew Y. Ng
Andrew Y. Ng Stanford University
Kristina Toutanova
Kristina Toutanova Google (United States)
Angel X. Chang
Angel X. Chang Simon Fraser University
Daniel Cer
Daniel Cer Google (United States)

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