Jackson Eli Reynolds Professor
  in Humanities,
Professor of Linguistics
Professor of Computer Science
Stanford University
  I study natural language processing and its application to the social and cognitive sciences. I am a past MacArthur Fellow and also work on the language of food.
Margaret Jacks 117
Stanford CA 94305-2150


TWITTER: @jurafsky



NLP group




Postdoc position available!


From Languages to Information

Tu/Thu 3:15 PM - 4:30 PM, Room 420-040

SPRING 2020 CS 384: Seminar on Social and Ethical Issues in Natural Language Processing

Even Earlier Courses

CS124:     YouTube lecture videos
2012 NLP MOOC w/Chris Manning:
    Youtube channel lecture videos


3rd edn. draft chapters!
Speech and Language Processing
Dan Jurafsky and James H. Martin

James Beard Award


Portelance, E., M. C. Frank, D. Jurafsky, A. Sordoni, R. Laroche. (2021). The Emergence of the Shape Bias Results from Communicative Efficiency. Proceedings of the 25th Conference on Computational Natural Language Learning (CoNLL). [PDF]

*San, N., *Bartelds, M., Browne, M., Clifford, L., Gibson, F., Mansfield, J., Nash, D., Simpson, J., Turpin, M., Vollmer, M., Wilmoth, S., & Jurafsky, D. (2021). Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages. ARSU 2021. [pdf].

Dorottya Demszky, Jing Liu, Heather Hill, Dan Jurafsky, and Chris Piech. (2021). Can Automated Feedback Improve Teachers' Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course. EdWorkingPapers. [pdf]

William Held, Dan Iter, Dan Jurafsky. (2021). Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. EMNLP 2021 [PDF]

Heidi Chen, Emma Pierson, Sonja Schmer-Galunder, Jonathan Altamirano, Dan Jurafsky, Jure Leskovec, Magali Fassiotto, and Nishita Kothary. 2021. Gender differences in patient perceptions of physicians' communal traits and the impact on physician evaluations. Journal of Women's Health, April 2021. 551-556. http://doi.org/10.1089/jwh.2019.8233

Mauriello M.L., Tantivasadakarn N., Mora-Mendoza M. A., Lincoln E. T., Hon G., Nowruzi P., Simon D., Hansen L., Goenawan N. H. , Kim J., Gowda N., Jurafsky D., Paredes P. E. (2021). A Suite of Mobile Conversational Agents for Daily Stress Management (Popbots): Mixed Methods Exploratory Study. JMIR Form Res 2021;5(9):e25294 doi: 10.2196/25294. [PDF].

Mauriello, M.L., Lincoln, E.T., Hon, G., Simon, D., Jurafsky, D., and Paredes, P.E. (2021)."SAD: A Stress Annotated Dataset for Recognizing Everyday Stressors in SMS-like Conversational Systems." In Proceedings of ACM CHI 2021 Conference on Human Factors in Computing Systems. Extended Abstract. [PDF]

Camp, N.P., Voigt, R., Jurafsky, D., and Eberhardt, J.L. (2021). The Thin Blue Waveform: Racial disparities in officer prosody shape institutional trust. Journal of Personality and Social Psychology.

Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, and Tatsunori Hashimoto. 2021. Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions. ACL 2021.

Kawin Ethayarajh and Dan Jurafsky. 2021. Attention Flows are Shapley Value Explanations. ACL 2021.

Michael Hahn, Dan Jurafsky, Richard Futrell. 2021. Sensitivity as a Complexity Measure for Sequence Classification Tasks. Transactions of the Association for Computational Linguistics (to appear), 2021. [paper] [bib]

Yasuhide Miura, Yuhao Zhang, Emily Tsai, Curtis Langlotz and Dan Jurafsky. 2021. Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). [paper, bib]

Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch and Dhanya Sridhar. 2021. Causal Effects of Linguistic Properties. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). [paper, bib]

Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer and Mike Lewis. 2021. Nearest Neighbor Machine Translation. International Conference on Learning Representations (ICLR), 2021. [paper].

K. Mahowald, M. Norris, D. Jurafsky. 2021. Concord begets concord: A Bayesian model of nominal concord typology. Proceedings of 95th LSA (2021).