Andrew Piper is Professor and William Dawson Scholar in the Department of Languages, Literatures, and Cultures at McGill University. He directs .txtlab, a laboratory for cultural analytics at McGill, and is editor of the Journal of Cultural Analytics.

His work focuses on applying the tools of data science to the study of literature and culture, with a particular emphasis on questions of cultural equality. He has on-going projects that address questions of cultural capital, academic publishing and power, and the the visibility of knowledge.

He is the author most recently of Can We Be Wrong? The Problem of Textual Evidence in a Time of Data (Cambridge 2020). This book explores the challenges of generalization when it comes to understanding literary behavior and the new evidentiary frameworks that digital methods afford. If you're interested in better grasping the limitations of current methods in the humanities and the advantages and opportunities that tools like machine learning make possible, then this book is for you.

Previous books include Enumerations: Data and Literary Study (Chicago 2018), which explores the application of new data-driven techniques to the study of topics including the role of punctuation in poetry, the matter of plot in novels, the study of topoi, the behavior of characters, the nature of fictional language, and the shape of a poet's career. His first book, Dreaming in Books: The Making of the Bibliographic Imagination in the Romantic Age (Chicago 2009), was awarded the Modern Language Association Prize for a First Book and honorable mention for the Harry Levin Prize from the American Comparative Literature Association. This was followed by Book Was There: Reading in Electronic Times (Chicago 2012), which chronicles the embodied dimensions of reading over the past two-thousand years.

His work has appeared in The Atlantic, The New Republic, The Guardian, Slate, Le Devoir, and he has appeared in interviews on the CBC.