School of Humanities and Sciences


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  • Thomas Mullaney

    Thomas Mullaney

    Professor of History

    Current Research and Scholarly InterestsThomas S. Mullaney is Associate Professor of Chinese History at Stanford University. He is the author of Coming to Terms with the Nation: Ethnic Classification in Modern China and principal editor of Critical Han Studies: The History, Representation and Identity of China’s Majority. He received his BA and MA degrees from the Johns Hopkins University, and his PhD from Columbia University under the direction of Madeleine Zelin.

    His most recent project, The Chinese Typewriter: A Global History, examines China’s development of a modern, nonalphabetic information infrastructure encompassing telegraphy, typewriting, word processing, and computing. This project has received three major awards and fellowships, including the 2013 Usher Prize, a three-year National Science Foundation fellowship, and a Hellman Faculty Fellowship. The book manuscript is about to be submitted for formal editorial review.

    He also directs DHAsia, a new Digital Humanities initiative at Stanford University focused on East, South, Southeast, and Inner/Central Asia. The program is supported by the Center for Spatial and Textual Analysis (CESTA). DHAsia 2016 will center around a series of intellectually intensive 3-day visits by a core group of scholars incorporating three components: (a) a 45-minute talk on their research; (b) a hands-on Digital Humanities clinic for faculty and graduate students (focused on the particular tool/technique/method/platform employed in their work); and (c) a schedule of one-on-one meetings with interested faculty and graduate student researchers.

    He is also the Founder and Editor-in-Chief of Dissertation Reviews, which publishes more than 500 reviews annually of recently defended dissertations in nearly 30 different fields in the Humanities and Social Sciences.

  • Mark Musen

    Mark Musen

    Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science

    Current Research and Scholarly InterestsThere are great opportunities for new discoveries and for ensuring the reproducibility of scientific results when experimental data—and descriptions of the methods used to generate and analyze those data—are available in public repositories. Our laboratory is studying the development of new methods to aid investigators in creating more comprehensive online descriptions both of their data and of their experiments that can be processed both by other scientists and by computers.