curriculum vitae
current role
Machine Learning Postdoctoral Fellow at Smithsonian Institution, Data Science Lab and the United States Holocaust Memorial Museum.
I have explored the ways in which we can ethically and reliably apply machine learning to archival material, particularly records that are sensitive in nature and multilingual. I have used the last four years to not only share my research via courses, talks and publications, but also to build tools and machine learning pipelines to help the USHMM and Smitshonian process, identify and extract important metadata from their collections. Many of these projects have resulted in open-source datasets, machine learning models, and Python packages.
Education
2020: Ph.D. in Medieval History at the University of Kentucky
2012: M.A. in History at Florida Gulf Coast University
2010: B.A. in History at Florida Gulf Coast University
books
Mattingly, William. (July 2023) Introduction to Python for Humanists. Routledge - Taylor and Francis.
peer-reviewed articles
Mattingly, William and Stephen Davis. (Forthcoming December 2024) Data as Practice: Alternate Modes of Learning in the Undergraduate and Graduate Digital Humanities Classroom. Companion to DH in Practice. Routledge.
Mattingly, William. (Forthcoming 2024) Python or R? Getting Started with Programming for Humanists. Compendium for Computational Theology.
Dikow RB, DiPietro C, Trizna MG, BredenbeckCorp H, Bursell MG, Ekwealor JTB, Hodel RGJ, Lopez N, Mattingly WJB, Munro J, Naples RM, Oubre C, Robarge D, Snyder S, Spillane JL, Tomerlin MJ, Villanueva LJ, White AE (2023) Developing responsible AI practices at the Smithsonian Institution. Research Ideas and Outcomes 9: e113334. https://doi.org/10.3897/rio.9.e113334.
Dikow, R. B., Ekwealor, J. T. B., Mattingly, W. J. B., Trizna, M. G., Harmon, E., Dikow, T., Arias, C. F., Hodel, R. G. J., Spillane, J., Tsuchiya, M. T. N., Villanueva, L., White, A. E., Bursell, M. G., Curry, T., Inema, C., Geronimo-Anctil, K. 2023. Let the records show: attribution of scientific credit in natural history collections. International Journal of Plant Sciences special volume in honor of Vicki Funk, 184, (5) 392–404. https://doi.org/10.1086/724949.
Johnson, K. P., Burns, P. J., Stewart, J., Cook, T., Besnier, C., & Mattingly, W. J. B. (2021). The Classical Language Toolkit: An NLP Framework for Pre-Modern Languages. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations (pp. 20-29). https://doi.org/10.18653/v1/2021.acl-demo.3
Besnier, C. and Mattingly, W. (2021) Named-Entity Dataset for Medieval Latin, Middle High German and Old Norse. Journal of Open Humanities Data, 7(0), p. 23. https://doi.org/10.5334/johd.36.
talks
“NLP in the Age of LLMs”, presented to The Chinese University of Hong Kong. (30 September 2024).
“Building Machine Learning Pipelines at Scale”, presented at the USHMM, (19 August 2024).
“Interrogating Digital Justice as Disaster Recovery”, presented at DH 2024, (8 August 2024).
“Teaching Machine Learning in the Humanities”, presented at DH 2024 (6 August 2024).
“Introduction to Retrieval Augmented Generation”, presented at TAP Institute (29 July - 2 August 2024).
“Introduction to Vector Databases”, presented at TAP Institute, (22 - 26 July 2024).
“The Role of spaCy in the World of LLMs”, presented at TAP Institute, (15 - 19 July 2024).
“From Capture to Engagement: Experiments in Using AI for Indexing, Named Entity Recognition, and More” presented at AI in Oral History Symposium (15 July 2024)
“AI in the Arts and Humanities”, presented at Society for Scholarly Publishing, (31 May 2024).
“Developing an NER model for the Holocaust”, presented at Holocaust Testimonies as Language Resources Conference, (20 May 2024).
“Where did the Holocaust happen? Locating place in testimonies through machine learning” co-presented at Quantifying the Holocaust, (15 May 2024).
“Developing Vector Databases for Semantically Querying Holocaust Material”, presented at the annual EHRI Colloquium. (5 May 2023).
“AI & Prompt Design”, presented to NISO as an 8-part series, (4 April - 23 May 2024).
“Text and Data Mining”, presented to NISO as an 8-part series, (12 October - 7 December 2023).
“LLMs and Higher Education”, presented to JSTOR (11 October 2023).
“Building Named Entity Recognition Pipelines”, presented at TAP Institute, (July 2023).
“Building Text Classification Pipelines”, presented at TAP Institute, (July 2023).
“Introduction to Natural Language Processing”, presented at TAP Institute, (July 2023).
“Multilingual Named Entity Recognition”, presented at TAP Institute, (June 2022).
“Data Management and Analysis in Python with Pandas”, presented at TAP Institute, (June 2022).
“Introduction to Natural Language Processing”, presented at TAP Institute, (June 2022).
“The Application of Machine Learning to Large Archives” presented at Smithsonian Institution,
(30 March 2022).
“Machine Learning and the Analysis of Historical Texts” presented at Virginia Tech 24 March 2022.
“Ancient and Medieval Text Analysis”, presented at TAP Institute, (June 2021).
“Applying Machine Learning in the Humanities”, presented at TAP Institute, (June 2021).
“The Challenges of Developing NER for Holocaust and Medieval Texts” presented at the AI4GLAM (February 2021).