William A. Ingram

Associate Professor
Associate Dean and Executive Director for Information Technology
University Libraries, Virginia Tech
Newman Library, 2320A Torgersen Hall
560 Drillfield Drive
Blacksburg, VA 24061
waingram@vt.edu

William A. Ingram, associate 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 dissertation 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 (LG-37-19-0078-19) to study the application of computational methods and resources to large corpora of electronic theses and dissertations.

News

June 2024 I have been awarded continued appointment and promotion to Associate Professor at Virginia Tech.
May 2024 Our journal article "Building Datasets to Support Information Extraction and Structure Parsing from Electronic Theses and Dissertations" has been published in the International Journal on Digital Libraries.
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 https://www.archives.gov/developer/artificial-intelligence-and-machine-learning-datasets 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."