World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
115
Citations
67522
World Ranking
187
National Ranking
109

Research.com Recognitions

  • 2020 - Fellow of the American Academy of Arts and Sciences
  • 2019 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Dan Jurafsky is affiliated with Stanford University in the United States and specializes primarily in computer science with a focus on artificial intelligence. Their research spans numerous subfields, including artificial intelligence, sociology and political science, computer vision and pattern recognition, general social sciences, and political science and international relations.

The scientist has contributed extensively to topics related to natural language processing techniques, topic modeling, speech recognition and synthesis, multimodal machine learning applications, computational and text analysis methods, speech and dialogue systems, and language and cultural evolution.

Recent publications by Dan Jurafsky include:

  • "On the Opportunities and Risks of Foundation Models" (2021), published in arXiv (Cornell University)
  • "Racial disparities in automated speech recognition" (2020), published in Proceedings of the National Academy of Sciences
  • "Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study" (2023), published in The Lancet Digital Health
  • "Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning" (2020), published in arXiv (Cornell University)

Key frequent co-authors collaborating with Jurafsky include Kawin Ethayarajh, Mirac Süzgün, Martijn Bartelds, Peter Henderson, and Tatsunori Hashimoto.

The most common venues for publication are:

  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • Findings of the Association for Computational Linguistics: ACL 2022
  • Proceedings of the Linguistic Society of America
  • The Lancet Digital Health

In addition to research articles, Dan Jurafsky has published a book titled Linguistic Theory and the Biblical Text in 2023 under Cambridge Semitic Languages and Cultures.

Dan Jurafsky has been recognized as a Fellow of the American Academy of Arts and Sciences since 2020 and as a Fellow of the American Association for the Advancement of Science since 2019.

Best Publications

  • Speech and Language Processing

    Dan Jurafsky;James H. Martin

  • Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

    Daniel Jurafsky;James H. Martin

  • Distant supervision for relation extraction without labeled data

    Mike Mintz;Steven Bills;Rion Snow;Daniel Jurafsky

  • Automatic labeling of semantic roles

    Daniel Gildea;Daniel Jurafsky

  • Cheap and Fast -- But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks

    Rion Snow;Brendan O'Connor;Daniel Jurafsky;Andrew Ng

  • On the Opportunities and Risks of Foundation Models.

    Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

  • Dialogue act modeling for automatic tagging and recognition of conversational speech

    Andreas Stolcke;Noah Coccaro;Rebecca Bates;Paul Taylor

  • Deep Reinforcement Learning for Dialogue Generation

    Jiwei Li;Will Monroe;Alan Ritter;Dan Jurafsky

  • Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change

    William L. Hamilton;Jure Leskovec;Dan Jurafsky

  • Word embeddings quantify 100 years of gender and ethnic stereotypes.

    Nikhil Garg;Londa Schiebinger;Dan Jurafsky;James Zou

  • Learning Syntactic Patterns for Automatic Hypernym Discovery

    Rion Snow;Daniel Jurafsky;Andrew Y. Ng

  • Adversarial Learning for Neural Dialogue Generation

    Jiwei Li;Will Monroe;Tianlin Shi;Sébastien Jean

  • Probabilistic relations between words: Evidence from reduction in lexical production.

    Daniel Jurafsky;Alan Bell;Michelle Gregory;William D. Raymond

  • Predictability Effects on Durations of Content and Function Words in Conversational English

    Alan Bell;Jason Brenier;Michelle L. Gregory;cynthia girand

  • A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

    Daniel Jurafsky;Daniel Jurafsky

  • Visualizing and Understanding Neural Models in NLP

    Jiwei Li;Xinlei Chen;Eduard H. Hovy;Dan Jurafsky

  • Deep Reinforcement Learning for Dialogue Generation

    Jiwei Li;Will Monroe;Alan Ritter;Michel Galley

  • Unsupervised Learning of Narrative Event Chains

    Nathanael Chambers;Dan Jurafsky

  • A Hierarchical Neural Autoencoder for Paragraphs and Documents

    Jiwei Li;Thang Luong;Dan Jurafsky

  • Studying the History of Ideas Using Topic Models

    David Hall;Daniel Jurafsky;Christopher D. Manning

  • Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

    A. Stolcke;K. Ries;N. Coccaro;E. Shriberg

Frequent Co-Authors

Christopher D. Manning
Christopher D. Manning Stanford University
Jiwei Li
Jiwei Li Zhejiang University
Jure Leskovec
Jure Leskovec Stanford University
James H. Martin
James H. Martin University of Colorado Boulder
Andrew Y. Ng
Andrew Y. Ng Stanford University
Wayne H. Ward
Wayne H. Ward University of Colorado Boulder
Michel Galley
Michel Galley Microsoft (United States)
Steven Bethard
Steven Bethard University of Arizona
Sameer Pradhan
Sameer Pradhan Vassar College
Ani Nenkova
Ani Nenkova Adobe Systems (United States)

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