Graduate Student Handbook: Center for Digital Humanities @ Princeton on Grad Student Handbook

Certificate Description

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The Graduate Certificate in Digital Humanities educates and credentials the next generation of researchers in cutting-edge theories, methods, and computational approaches that are transforming fields ranging from medieval history to media studies. Certificate students have the opportunity to expand their methodological toolkit, to engage in vital debates on the future of AI, and to build a community of praxis currently expanding the applications of humanistic thought.

The Certificate equips Princeton graduate students to be interdisciplinary, forward-thinking researchers in a competitive academic job market. Certificate students are primed for careers on the tenure track as well as a broader range of professional futures in cultural heritage institutions, industry, or the public sphere.

Eligibility

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Admission to the Certificate is open to PhD students in any academic division who are interested in applying concepts from critical data studies and media studies, or in using quantitative, data-intensive, or computational methods in their research. Students must be in good academic standing and have the written support of their academic advisor or the director of graduate studies in their department. There are no prerequisites.

Please note that the CDH is not a degree-granting unit. In order to join the Graduate Certificate in DH, students must first apply and be admitted to a home department’s PhD program via the Graduate Admission Office.

Requirements

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All details on the requirements for the Graduate Certificate in Digital Humanities are documented on the Graduate School Fields of Study page.

For questions on these requirements or requests for exemptions, please contact cdh-info@princeton.edu

Enrolling in the Certificate

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Once you are confident you are eligible for the Certificate and have reviewed its requirements, you are ready to apply! Click the button below to complete a brief Google Form.

Enroll in the Certificate

You will be asked some basic information including:

Your department
Progress toward your PhD
Advisor’s name
Whether we have permission to contact that advisor about your enrollment in the Certificate
Whether you have completed any of the Certificate requirements

Graduate Courses

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Princeton graduate courses (500-level or above) can be cross-listed with a CDH (Computational & Data Humanities) subject code. This subject code is administered by the Center for Digital Humanities. A 500-level course that is cross-listed with the CDH subject code signifies that the CDH has approved this course to fulfill the elective requirement for the Certificate Description.

Elective courses that count toward the certificate place humanistic research in meaningful and sustained dialogue with methods and concepts in data science, computation, and emerging technologies (e.g. generative art and synthetic text). These classes either a) teach critical and historical frameworks for studying computation, including those informed by data feminism, algorithmic bias frameworks, media theory, and tech justice, or b) require assignments applying data, computational, and quantitative methods to humanities research domains, or c) both. Please see below for categories of courses and examples of how they mix these critical and practical methodologies.

Colloquium

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Every April, the Commons Visualization Lab hosts a Joint Graduate Certificate Colloquium in Data and Computation. The joint colloquium is an opportunity for PhD students completing certificates in Computational Science & Engineering, Statistics & Machine Learning, and Digital Humanities to present their dissertation research in a way that showcases the use of data and computation across the disciplines.

Students interested in presenting should contact: cdh-info@princeton.edu

The presentations are designed to be accessible to the broader University community with an interest in any domain touched by data, computation or statistics and machine learning. Each research presentation runs approximately 20 minutes including time for questions from the audience.

Alumni

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Recipients of Graduate Certificate in DH#

Since it was launched in 2023, the following students have received the Graduate Certificate in DH.

Year	Name	Department
2023	Gian Rominger	East Asian Studies
2024	Gyoonho Kong	German
2025	Kate Clairmont	English
2025	Stephanie Luescher	Near Eastern Studies
2026	Rachel Richman	Near Eastern Studies

Career Outcomes#

Since it was founded in 2014, the CDH has trained hundreds of graduate students across our many other co-curricular offerings. These students hail from all fourteen PhD-granting humanities departments at Princeton plus Anthropology, Architecture, Computer Science, History, History of Science, Politics, and Sociology. These students have gone on to careers in higher education, libraries, policy, nonprofits, and the tech industry.

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There is no one right way to sequence the workshops, classes, and fellowships offered by the CDH and our campus partners like Digital Scholarship (DiScho) and Research Computing. But the diagram below suggests some pathways that PhD students might want to follow: from introductory classes, to project-based learning, to advanced training, and finally capstone presentations.

Graduate Fellowship

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The CDH Graduate Fellowship is a one-semester studio for workshopping research in progress. The program welcomes PhD students into the community of Princeton digital humanities researchers and provides the mentorship and support necessary to begin employing computational and data-driven methods in their work. Over the course of one semester, fellows will articulate research questions and identify goals for small-scale, standalone projects or for components of larger projects (e.g. a dissertation). As a cohort, fellows will explore tools, methods, and best practices that will benefit them throughout their careers. No prior technical skills are required, but a familiarity with the landscape of digital humanities, cultural analytics, media theory, or data science is a plus.

Graduate Training Grant

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The CDH supports Princeton graduate students who would like to expand their knowledge of data-driven and computational approaches to the humanities by taking advantage of courses, workshops, summer schools, institutes or other training opportunities offered outside of Princeton. Recipients should learn new technical or methodological skills, receive professional development training, and/or make connections in the digital and computational humanities communities.

For a non-exhaustive list of institutes our students have attended in the past, see: External Institutes and Workshops

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The Center for Digital Humanities is pleased to announce that we are accepting nominations for the Digital Humanities Dissertation Prize, which recognizes exceptional doctoral work with a digital humanities component by recipients of Princeton PhDs. Applicants may self-nominate, as long as they secure a letter of recommendation from a Princeton faculty member. The prize carries an award of $2,000.

For a list of past winners and details on the current call for applications, visit the CDH website.

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The CDH collaborates with a number of Princeton campus units at the intersection of data, computation, and cultural criticism. Graduate students may want to explore the other offerings from:

PUL Digital Scholarship, a one-stop-shop introducing researchers to tools for mapping, text mining, data visualization, and digital exhibits.
Research Data Service, which provides expert guidance curating and publishing data.
Research Computing, which maintains the university’s cloud computing infrastructure and offers workshops on a range of topics.
The AI Lab, which supports and expands the scope of AI research at Princeton. See their Resource Guide (PU login required).
PUL Maps & Geospatial Information Center offers specialized guidance for students working with maps.
MakeNet, a consortium of the university’s maker spaces. Resources include 3D scanning and printing, book binding, and more.
Social scientists should refer to our partners at the Data Driven Social Science Initiative
For help creating a website, see PUL’s Project Website Support and the options provided by OIT’s Web Development Services (WDS)
For suggestions and support creating a digital or data-driven classroom assignments, see the McGraw Center’s Digital Assignment Guide
For world-class guidance on professional development, please visit GradFUTURES, “a dynamic hub that empowers graduate scholars, researchers, and leaders to succeed in graduate school and craft futures that are fully their own.” The CDH often partners with GradFUTURES on hosting University Administrative Fellows (UAF’s). Please contact us if you are interested in this possibility.

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Students looking to learn more about using data and computation in their research can find many sources of workshops and training around campus, including:

Digital Scholarship Foundations Program (DiScho). The most recent series was devoted to “…version control, data wrangling, coding templates, web publishing, and more as they transform research into spatial data and build their own interactive map.” Topic varies by semester.
A list of upcoming PUL workshops and events related to “data & computation,” “publishing”, or “maps & GIS” is available at this LibCal link
Data Driven Social Science hosts their own workshops
AI Lab hosts events and workshops. The latter are typically posted in the #announcements channel on their Slack.
Research Computing offers workshops and live trainings throughout the academic year and summer.

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Relevant reading groups on AI, DH, technology, and society can be found around campus, including:

LLM Collective: hands-on experiments and conversations, co-hosted by PICSciE, CSML, DDSS
Integrated Ethics in CS (undergrad-focused)
Center for IT Policy (CITP)
- Bias in AI Reading Group
- Lunchtime seminar series
- CITP Book Club, currently reading Breakneck: China’s Quest to Engineer the Future by Dan Wang

Getting Started in DH

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If you’re new to DH, please check out these sources for DH News, Ideas, and Community. You should also free to book a consultation with a CDH researcher at any time.

Defining DH is a practice as old as the field itself, even to the point of parody.¹ Some of our favorite definitions at the CDH revolve around a chiasmus: the use of computational methods in the humanities, and the humanistic critique of emerging technologies. For Schüller-Zwierlein et al.,

Sources for DH News & Ideas

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Knowledge Bases#

DH Now, “an experimental, edited publication that highlights and distributes informally published digital humanities scholarship and resources from the open web.” Great place for CFPs, job calls, and recent research highlights.
Notes in the Computational Humanities is a definitive resource for conferences, fellowships, prizes, journals, tutorials, and more, maintained by the Columbia Narrative Intelligence Lab.

Communities & Conferences#

Association for Computers and the Humanities (ACH), the US-based professional organization for DH. Offers professional development events and an annual conference (virtual, open registration).
Alliance of Digital Humanities Organizations (ADHO), the international umbrella organization that hosts the annual DH conference, each year on a new continent.
Digital Humanities Summer Institute (DHSI), long-running, one- or two-week summer training program held in Montreal for newcomers and advanced scholars alike.
Computational Humanities Research (CHR), annual conference on computational approaches to the humanities. Typically hosted in Europe.

Bluesky, where most of the academic DH conversation now happens. See especially Amanda Visconti’s Bluesky Quickstart Guide, including its “starter packs” of DH scholars to follow. Pam Lach also has a starter pack of Bluesky users for DH in Libraries.
Digital Humanities Slack, “a set of informal, connected chat rooms for the digital humanities and related interests, with over 50 “channels” (chat rooms) devoted to specific topics such as DH teaching, coding, library work, and conferences.”

Newsletters#

Academics#

Humane Ingenuity, Dan Cohen
Atlanta Interdisciplinary AI Network (AIAI)
Generative History, Mark Humphries (Substack)
Res Obscura, Ben Breen (Substack)
Jason Heppler
The Stone & the Shell, Ted Underwood

Tech Observers & Experimenters#

Blood in the Machine, Brian Merchant (Substack)
Cybernetic Forests, Eryk Salvaggio (Substack)
Ethan Mollick, One Useful Thing (Substack)
Kyle Chayka (Substack)
Maggie Appleton
Gary Marcus (Substack)
Wild Information, Claire L. Evans
Astral Codex Ten

External Institutes and Workshops

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These are the institutes and workshops our students have attended in the past, with support of a Graduate Training Grant:

Digital Resources and Methods (DREAM Lab), University of Pennsylvania
Digital Humanities Summer Institute (DHSI), Montreal
Digital Humanities at Oxford Summer School, UK
European Summer University in Digital Humanities, Besançon, France. “A two-week intense university-level program in several key DH areas.”
ATRIUM Summer School, Athens, Greece
Critical AI Literacies for Resisting and Reclaiming, Radboud Universiteit
London Rare Books School
Hellenic Studies Summer Institute (Athens)
IGEL Training School, virtual workshop on Empirical Literary Studies
Northeastern AI + Data Ethics (AIDE) Summer, intended for advanced grad students in STEM and philosophy
EPFL’s Applied Data Science (online program, self-paced, certificate granting)

List of AI Research Centers

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AI — its research applications, its political economy, and its underlying technology — are evolving at a breakneck pace. Follow these groups to keep up to date.

Community- and Justice-Focused#

AI Now Institute
Algorithmic Justice League, Joy Buolamwini
Knowing Machines project, including this legal explainer on generative AI
Atlanta Interdisciplinary AI Network, Lauren Klein
Distributed AI Research (DAIR) Institute, including their Data Workers’ Inquiry project.
AI for the People: “To represent the interests of black communities within high level policy meetings within government, industry and led academic research into the development of rights respecting AI.”
AI Accountability Lab
Centre for the Governance of AI
All Tech is Human
Ada Lovelace Institute
TechTonic Justice

University-Based or Research-Focused#

UC Berkeley Center for Human-Compatible AI (CHAI)
Berkeley Machine Intelligence Research Institute (MIRI), an organization that works on better formal characterizations of the AI safety problem. Founded by Eliezer Yudkowsky.
Stanford Center for Research on Foundation Models
Stanford Center for Human-Centered Artificial Intelligence (HAI)
Stanford’s One Hundred Year Study on AI, releasing reports every 5 years. 2016, 2021 released so far.
Jokingly: Center for the Alignment of AI Alignment Centers

Mapping These Groups & Their Arguments#

Mapping AI focuses on the US AI policy landscape.
Michel Justen’s “A Guide to the AI Tribes” outlines the schools of thought on AI and its politics.

Sources for Humanities Data

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Given the complexity and nuance of our sources, it used to be a challenge to find high-quality data in the humanities. But with the recent proliferation of journals devoted to the peer-reviewed publication of humanities data, that is no longer the case.

Sources for humanities data, organized by discipline and annotated with information about data format and collection practices, can be found through the resources below:

Responsible Datasets in Context, eds. Fernandez, Posner, Preus, Singh, & Walsh
Post45 Data Collective, eds. Walsh, Manshel, Porter.
Amanda Wyatt Visconti, “Interesting digital humanities data sources,” UVA Scholars Lab Blog, (August 26, 2025).
Matt Lavin’s Humanities Data
Journal of Open Humanities Data
Jeremy Singer-Vine’s Data Is Plural archive
The Pudding’s data repository
List of Selected Datasets and Corpora for the Humanities, maintained by CUNIL Notes in the Computational Humanities
Datasets at the Library of Congress: A Research Guide also paired with Digital Scholarship at the Library of Congress: A Research Guide and Data for Exploration
TextGrid Repository, “an extensive searchable and adaptable corpus of XML/TEI encoded texts and images.”
CDH-curated list of humanities datasets
You can also see the annual DH Award nominees and winners for Best DH Dataset or Model.

Graduate Student Handbook: Center for Digital Humanities @ Princeton on Grad Student Handbook

Certificate Description

Eligibility

Requirements

Enrolling in the Certificate

Graduate Courses

Colloquium

Alumni

Recipients of Graduate Certificate in DH#

Career Outcomes#

Graduate Fellowship

Graduate Training Grant

Getting Started in DH

Sources for DH News & Ideas

Knowledge Bases#

Communities & Conferences#

Social Media#

Newsletters#

Academics#

Tech Observers & Experimenters#

External Institutes and Workshops

List of AI Research Centers

Community- and Justice-Focused#

University-Based or Research-Focused#

Mapping These Groups & Their Arguments#

Sources for Humanities Data