Humanities Research Software Engineering
Pushing the Frontier of Humanities Research: Collaborative Research Partnerships from First Idea to Scholarly Publication.
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At the CDH, research software engineering is a deeply collaborative and truly interdisciplinary endeavor.
Our team of research software engineers and project managers are scholars and researchers, with MAs and PhDs in English, History, Computer Science, and East Asian Studies, who specialize in the computational aspects of the digital humanities. Through integrated project design and management support, we collaborate with Princeton faculty to design and build research projects with and about cultural data, critical theories, and computational systems.
We produce a wide variety of scholarly outputs, including software packages, datasets, research interfaces, and peer-reviewed articles.
In 2026-2027, CDH RSEs are collaborating on 12 faculty projects across 7 departments.
Featured projects
Transcribe Lab
AI infrastructure shaped by and for scholars for transforming handwritten and complex historical sources into machine-readable text, and for learning to use these methods critically.
MuSE (Multilingual Semantic Embeddings)
Linking concepts in music-theoretical texts across languages
remarx
A text-reuse detection tool enabling scholars to surface and connect related texts across documents, regardless of language.
Princeton Prosody Archive
Inviting users to rethink poetry's past through a collection of historical prosodic works
Meet the RSE team
Rebecca Sutton Koeser
Lead Research Software Engineer
Laure Thompson
Research Software Engineer
Hao Tan
Research Software Engineer
Christine Roughan
Digital Humanities Project Manager
Jeri Wieringa
Assistant Director
Connect with us!
We want to hear from you about your project! To start the conversation, sign up for a consultation.
We publish an annual Call for Proposals to identify and select new collaborative projects. Proposals are evaluated by our Executive Committee and are selected based on alignment with research priorities and the expertise and availability of our current team. Subscribe to the newsletter to receive notice of upcoming calls.
Collaborative Research Partnerships
Faculty are welcome to apply to work with the CDH Research Software Engineering team!
Transcribe Lab Fellows
Work with the CDH to transform historical and hard to read texts into data.
Featured software, datasets, and publications
The CDH RSE team produces open source software, datasets, and scholarly publications as part of our collaborative research projects.
All software is released under the Apache 2 open-source license and is available on GitHub.
Princeton Prosody Archive Found Poems Dataset
Princeton Prosody Archive Found Poems Dataset
Structured dataset of poems found and identified within the Princeton Prosody Archive.
Laure Thompson et al., Princeton Prosody Archive Found Poems Dataset, May 6, 2026, https://doi.org/10.5281/zenodo.20044417.
corppa
corppa
Software for working with the Found Poems data, based on the Princeton Prosody Archive.
Rebecca Sutton Koeser et al., Corppa Python Package, May 12, 2026, https://doi.org/10.5281/zenodo.20141843.
remarx
remarx
In-progress research software developed for the CDH project Citing Marx. The primary purpose of the initial version of this software is to identify quotes of Karl Marx's Manifest der Kommunistischen Partei and the first volume of Das Kapital within articles published in Die Neue Zeit between 1891 and 1918.
Initial release: Version v1.0, January 2026.
Princeton Geniza Project Dataset
Princeton Geniza Project Dataset
Data from the Princeton Geniza Project, structured for computational research.
Marina Rustow et al., “Princeton Geniza Project Dataset,” version v1.0.0, with Moshe Yagur et al., Zenodo, July 8, 2025, https://doi.org/10.5281/ZENODO.15839056.
Data Essay for the PGP Dataset
Data Essay for the PGP Dataset
Dataset essay on the history and structure of the Princeton Geniza Project.
Rebecca Sutton Koeser and Marina Rustow, “Princeton Geniza Project datasets,” Journal of Cultural Analytics 11, no. 3 (2026), https://doi.org/10.22148/jca.1084.
viapy
viapy
Python module for interacting with Virtual International Authority File (VIAF) data and APIs, with optional Django integration. Developed for use in multiple projects.
Initial version 0.1 released October 2017; v0.3 released April 2024.
djiffy
djiffy
Python module for use with the Django web framework to index and display IIIF Presentation manifests for digitized content. Developed to integrate Princeton University Library (PUL) digitized content for Derrida’s Margins and The Winthrop Family on the Page.
Initial version 0.1 released June 2017; version 0.9 released August 2024.
Related posts
Journal of Cultural Analytics publishes data essay on Cairo Geniza, bridging medieval Middle East with data science and AI
1 September 2026
Making Research Easier to Save: A Guide to Zotero Integration for Academic Websites
12 November 2025
Hao Tan
