Special Collections is pleased to have recently processed March Fong Eu’s archive, and to make available digitized recordings of her personal interview tapes. The papers of March Fong Eu are now open for research. The papers may be accessed here: https://searchworks.stanford.edu/view/9378418.
The Frank Y. Chuck papers are now open for research. This collection consists of materials relating to the life and career of Frank Y. Chuck, a noted research chemist and one of Stanford University’s earliest graduates of color. Included are academic transcripts, diplomas, domestic and international patents, professional papers, notebooks, correspondence, photographs that feature Stanford’s Chinese American student community from the 1920s, and an oral history interview transcript.
The Stanford Libraries recently acquired a manuscript collection dealing with the planning and preparation for the California Himalayan Expedition of 1954, created by Stanford alumnus Dr. Lawrence Swan (1922-1999)
How many of us first developed an understanding of the Indian subcontinent and its peoples from the writings of Vikram Seth, Salman Rushdie or Rohinton Mistry? Their stories, A Suitable Boy, Midnight's Children and A Fine Balance, introduced the rest of the world to the socio-political tensions fomenting in India since its independence from Britain in 1947.
The Spotlight exhibit on John W. Gardner provides a glimpse at his life and distinguished career in public service, as well as his time at Stanford as a student, trustee, professor, and mentor.
We are delighted to join Harvard University and the University of Manchester again on a collaborative venture over the next 18 months (2021-2022) funded by the Andrew W. Mellon Foundation grant, Email Archives: Building Capacity and Community managed by the University of Illinois.
The ePADD development team is excited to announce the release of version 8!
ePADD is free and open source software developed by Stanford Libraries' Special Collections & University Archives that uses natural language processing and machine learning to support archival appraisal, processing, discovery, and delivery for email of historical or cultural value.
Improved Performance for Large Collections
