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Lauren KleinWinship Distinguished Research Professor | QTM & English

Biography

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Lauren Klein is Winship Distinguished Research Professor and Associate Professor in the departments of Quantitative Theory & Methods and English at Emory University. She also serves as director of the Emory Digital Humanities Lab and PI of the Mellon-funded Atlanta Interdisciplinary AI Network. Before moving to Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. Klein’s research brings together computational and critical methods in order to explore questions of gender, race, and justice. She is the author of An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020) and, with Catherine D’Ignazio, the award-winning Data Feminism (MIT Press, 2020). With Matthew K. Gold, she edits Debates in the Digital Humanitiesa hybrid print-digital publication stream that explores debates in the field as they emerge. Her work has appeared in leading humanities journals including PMLA, American Literature, and American Quarterly; and at technical conferences including ACLEMNLP, and IEEE VIS. Her research has been supported by grants and fellowships from the ACLS, the NEH, and the Mellon Foundation.

Education

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  • PhD, English, City University of New York, 2011
  • M.Phil, English, City University of New York, 2006
  • BA, Literature (English and French), Harvard University, 2000

Research

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Digital Humanities, Data Justice, Data Studies, Quantitative Literary Studies

Selected Publications

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Lauren Klein recently published Debates in the Digital Humanities 2023 with the University of Minnesota Press. More info on the series can be found at: https:/heaters.gc.cuny.edu 

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Lauren is the co-author of Data FeminismWinner of the Modern Language Association Prize for Collaborative, Bibliographical, or Archival Scholarship, 2022.

Data Feminism

She has also the author of, An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020) 

 image of journal cover

Teaching

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  • QTM 310: Data Justice
  • QTM 340: Practical Approaches to Data Science w/Text
  • QTM 385: Special Topics in QTM
  • QTM 490W: Seminar in QTM