William A. Ingram,
assistant professor at Virginia Tech, is associate dean and
executive director for information technology in the University Libraries.
Ingram's research involves devising methods for computational
analysis and use of the large digital collections held by libraries
and archives. He is especially interested in electronic theses and
dissertations. Because they are long and contain multiple
chapters, they more resemble books than research articles. His aim is
to use methods for information extraction, classification, and
summarization to uncover the knowledge and data buried in this rich
corpus of graduate research to facilitate its discovery and equitable use.
Ingram received a B.A. in cognitive science from the
University Of Virginia and
an M.S. in Library
and Information Science
from the University of Illinois at
Urbana-Champaign in 2008. Since then, he has been involved in
projects and services related to scholarly communication,
digital preservation, repositories and
digital libraries. He is currently
pursuing a Ph.D. in Computer Science at
Virginia Tech, under the supervision of Professor Edward A. Fox, with a
focused on the application of
NLP and machine/deep learning to large-scale scholarly data.
In 2019, he was awarded a 3-year
National Digital Infrastructures research grant from the
Institute of Museum and Library Services
to study the application of computational methods and resources to
large corpora of electronic theses and dissertations.
- October 2023 Our paper titled "ETDPC: A Multimodality Framework for Classifying Pages in Electronic Theses and Dissertations" has been accepted for presentation at the Thirty-Sixth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24).
- June 2023 Our long paper, "Integrated Digital Library System for Long Documents and their Elements," has been nominated for Best Student Paper Award at JCDL 2023.
- June 2023 Our short paper, "MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries," is a Best Short Paper nominee at JCDL 2023.
- March 2023 Panel proposal accepted at JCDL 2023, "AI and Public Archives: Collaborative Leadership for Responsible Adoption."
- March 2023 Paper accepted at Sci-K 2023, co-located with The Web Conf 2023. Congratulations Aman!
- November 2022 Paper accepted at the 7th Computational Archival Science (CAS) Workshop, part of IEEE Big Data 2022. Congratulations Bipasha!
- September 2022 Paper accepted at the ETD 2022 Symposium in Novi Sad, Serbia. Congratulations Aman!
- April 2022 I will be co-leading a workshop in May on Leading the Future of AI and Public Archives with NARA, Library of Congress, and the Smithsonian.
- March 2022 Paper accepted by 2nd International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K) co-located with the 2022 Web Conference. Congratulations Lamia!
- February 2022 Report on Virginia Tech-NARA workshop series on AI deposited in VTechWorks. http://hdl.handle.net/10919/108067
- November 2021 Poster accepted at IEEE BigData. Congratulations Sami!
- August 2021 One short and one long paper accepted at JCDL'21.
- April 2021 VT-NARA workshop kicks off. Sponsored by the Andrew W. Mellon Foundation, Virginia Tech
and the U.S. National Archives and Records Administration are hosting a workshop series on "Ensuring Scholarly Access to Government Records and Archives"
April 9, 16, 23, 30, and May 7.
Visit https://lib.vt.edu/research-teaching/computational-archives-workshop.html for updates and
for program informaion.
- February 2021 Project briefing webinar accepted for CNI's Spring 2021 Virtual Meeting.
- November 2020 VT-NARA workshop rescheduled for Spring '21, will be held virtually.
- October 2020 Project briefing webinar accepted for CNI's Fall 2020 Virtual Meeting.
- April 2020 Poster accepted at JCDL'20.
- April 2020 Paper accepted for Practitioners Track at JCDL'20.
- March 2020 VT-NARA workshop postponed due to COVID-19.
- February 2020 Proposal accepted for half-day tutorial on Preparing Code and Data for Computational Reproducibility at JCDL'20.
- February 2020 Article accepted in Data and Information Management journal.
- January 2020 Grant awared (1910-07229)
for "Ensuring Scholarly Access to Government Records and Archives" by Andrew W. Mellon Foundation
to support a convening of experts to address machine-learning techniques to enhance public access to government records.
- October 2019 Nominated to join NDLTD Board of Directors.
- October 2019 Project briefing accepted for the CNI meeting in Washington, DC on December 9-10, 2019.
- August 2019 Paper on ETDs and workshop on computational reproducibility accepted for ETD 2019.
- June 2019 Received National Leadership Grants for Libraries Program award (LG-37-19-0078-19)
for the project "Opening Books and the National Corpus of Graduate Research."