Dr. Ryan Heuser
- email: rj416@cam.ac.uk
- profiles: CDH; GitHub; Google Scholar
About me
I am Assistant Professor of Digital Humanities at the University of Cambridge, where I teach for Cambridge Digital Humanities and the Faculty of English. I am a literary historian and computational humanist with fifteen years of experience in researching and teaching in the digital humanities.
My research and pedagogy span topics from the history and theory of DH to its methodological groundings in data science and visualization, natural language processing, network theory, machine learning, and large language models. My work focuses on computational approaches to prosody and rhythm, literary and intellectual history, and the history and impact of artificial intelligence on language.
I completed my PhD in English from Stanford University in 2019, where I was a founding member of the Stanford Literary Lab and its Associate Research Director from 2011 to 2015. From 2019-2022 I was Junior Research Fellow in King’s College, Cambridge, where I supervised students in English literature and Practical Criticism, taught workshops in the Center for Digital Humanities, and helped to review and establish its MPhil program. From 2022-2024 I was Research Software Engineer in Princeton’s Center for Digital Humanities.
You can also find me on CDH, Github, Google Scholar, or by email at rj416@cam.ac.uk.
Projects
Generative Humanities
Ongoing research project beginning from the conviction that, just as digital humanities became necessary in order to theorize the rising digitisation practices in the 1980s and ’90s, a ‘generative humanities’ has become necessary to theorize rising generative AI practices in the 2020s. A first research article is forthcoming in October 2025: ‘Generative Formalism: Measuring Formal Stuckness in AI Verse’ (Journal of Cultural Analytics, special issue on Computational Formalism forthcoming Oct 2025). It theorizes a generative formalism, practicing it in a comparative distant reading of historical and generative poetic corpora, which identifies a persistent ‘formal stuckness’ on strict rhyme and meter in AI verse – a kind of formal gravition recombining historical cultural production for its own computational-aesthetic ends. The project is currently transforming into a collaborative grant proposal on ‘slop,’ extending the analysis of formal stuckness from poetry to prose, art, music, and video.
Abstraction: A Literary History
My first book project, Abstraction: A Literary History, traces a slow-moving rise and fall in abstract language across centuries of literary history. Mixing close and distant reading, the book uncovers how these changes in literary semantics mediate changes in social organization. I focus on three literary forms of abstract language: ‘abstract style’, in the syntactic symmetries and semantic formulae of the periodical essay; ‘abstract persons’, in the personified abstractions of the mid-century ode; and ‘abstract realism’, in the “tell, don’t show” narration of the early realist novel. Through this history and framework, the book also aims to recuperate abstraction as both a method and an object of literary study.
- 2020-02-18: “Abstract Realism” (visual summary of the chapter on fiction)
Antimetricality
I am working with Arto Anttila and Paul Kiparsky, metrical phonologists at Stanford, to design tools to evaluate the ‘antimetricality’ of a text: the degree to which its stress patterns depart from any known metrical pattern. Such measurements of metrical ‘tension’ or ‘ambiguity’ have a history: prose most distances itself rhythmically from verse at the height of the eighteenth century. We have a pre-print of a paper available here.
2018-04-20: “The Rise and Fall of Antimetricality”
Publications
“Generative Formalism: Measuring Formal Stuckness in AI Verse.” Journal of Cultural Analytics, special issue on Computational Formalism. Forthcoming Oct 2025.
“Computational Hermeneutics: Evaluating Generative AI as a Cultural Technology.” SSRN, 1 Aug 2025. (Co-authored with Cody Kommers et al).
“Computing Koselleck: Modeling Semantic Revolutions, 1720-1960.” Explorations in the Digital History of Ideas. Ed. Peter de Bolla. Cambridge University Press. 2024.
“Enlightenment Entanglements of Improvement and Growth.” Explorations in the Digital History of Ideas. Ed. Peter de Bolla. Cambridge University Press. 2024. (Co-authored with Peter de Bolla and Mark Algee-Hewitt).
“Mapping London’s Emotions.” New Left Review 101 (2016): 63-91. (Co-authored with Franco Moretti and Erik Steiner).
“Mapping the Emotions of London in Fiction, 1700-1900: A Crowdsourcing Experiment.” Literary Mapping in the Digital Age. Ed. David Cooper, Chris Donaldson, and Patricia Murrieta-Flores. Ashgate. 2016. (Co-authored with Mark Algee-Hewitt, Van Tran, Annalise Lockhart, and Erik Steiner).
“Learning to Read Data: Bringing out the Humanistic in the Digital Humanities.” Victorian Studies 54.1 (2011): 79-86. (Co-authored with Long Le-Khac).
Reprinted in Canon/Archive: Studies in Quantitative Formalism from the Stanford Literary Lab, ed. Franco Moretti (New York: n+1, 2017):
“The Emotions of London.” Stanford Literary Lab 13 (2016). (Co-authored with Franco Moretti and Erik Steiner).
“Canon/Archive: Large-scale Dynamics in the Literary Field.” Stanford Literary Lab 11 (2016). (Co-authored with Mark Algee-Hewitt, Sarah Allison, Marissa Gemma, Franco Moretti, and Hannah Walser).
“On Paragraphs: Scale, Themes, and Narrative Form).” Stanford Literary Lab 10 (2015). (Co-authored with Mark Algee-Hewitt and Franco Moretti).
“Style at the Scale of the Sentence.” Stanford Literary Lab 5 (2013). (Co-authored with Sarah Allison, Marissa Gemma, Franco Moretti, Amir Tevel, and Irena Yamboliev).
“A Quantitative Literary History of 2,958 Nineteenth-Century British Novels: The Semantic Cohort Method.” Stanford Literary Lab 4 (2012). (Co-authored with Long Le-Khac).
“Quantitative Formalism: an Experiment.” Stanford Literary Lab 1 (2011). (Co-authored with Sarah Allison, Matthew Jockers, Franco Moretti, and Michael Witmore).
Archive
Word Vectors in the Eighteenth Century
This page is meant as a set of links and resources related to my work using word vectors to study eighteenth-century literature. This work asks the question: how can new vector-based models of semantics reveal the historicity of specific configurations of meaning in eighteenth-century literature? Most of this work is published serially as blog posts, linked below. The later of these are “slideshow essays”-experiments with the forms of visual rhetoric that work so well in the digital humanities-rather than traditional blog posts. There is also a video of a talk I’ve given about this work. Lastly, I’ve uploaded several word2vec models I’m using, trained on a corpus of eighteenth-century literature; and linked to some relevant code (more code will be coming soon).
2016-04-14: Part 1. Concepts
2016-06-01: Part 2. Methods
2016-09-10: Part 3. From Fields to Vectors
2016-09-25: Part 4. Semantic Networks
Graphs
2020-03-14: Tracing types of semantic change
2020-03-06: Measuring anthropomorphism
2020-02-24: Posted talk to King’s College as scroll-based page
2020-01-29: A linguistic map of the canon
2020-01-16: Clarissa under the microscope
2019-11-18: Academic job numbers in English literature (updated)
2019-10-13: Academic job numbers in English literature
2019-08-28: Figure 1 of my dissertation
2019-02-07: Measuring personification
2018-11-05: Agency Index
2018-07-12: Character space in Sense and Sensibility
2018-04-17: Anti-metricality
2018-01-30: Abstraction vs. judgment
2018-01-23: Computational Keywords
2017-11-06: Abstraction vs. agency
2017-09-26: Sociography of the 18th century print market
2017-07-28: Transformation of ‘labour’
2017-07-13: Understanding OCR errors
2017-07-03: Most reprinted 18th century texts
2017-06-23: Corpus vs. bibliography
2017-06-15: Exponential rise of print market in 18th century
2017-04-28: Computational model takes standardized test
2017-03-26: World literary trends (part 2)
2017-03-25: World literary trends (part 1)
2017-12-18: ELIZA’s descendants
2016-09-15: Semantic networks
2016-06-16: Semantic fields in vector space
2016-06-15: Diachronic semantic networks
2014-06-09: Reading at meso-scale with Moby-Dick
Tools
Prosodic: A metrical-phonological parser, written in Python. For English and Finnish, with flexible language support.
Poesy: Tools for poetic analysis (stanzaic, metrical, and rhyme forms), written in Python.
LLTK: Literary Language Toolkit (LLTK): corpora, models, and tools for the digital humanities, in Python.
Slingshot: Python wrapper for MPI to “slingshot” a Python or R function across a large dataset.
HashStash: Easy file-based store for caching arbitrary data
Teaching
- ‘Distant Reading’, MPhil seminar in Digital Humanities, U Cambridge
- ‘Generative AI: Theory and Practice’, MPhil seminar in Digital Humanities, U Cambridge
- ‘Critical Technical Practice’, MPhil lectures in Digital Humanities, U Cambridge
- ‘Practical Criticism and Critical Practice’, BA in English, King’s College, U Cambridge
- ‘Ballad, Sonnet, Lyric, Line’, PhD seminar in English, Princeton U (with Meredith Martin)
- ‘Literary Text Mining’, BA in English, Stanford U
CV
- See here