After a career spanning academia, technology, and entrepreneurship, I retired from Apple in June 2026. I joined Apple in 2021 as a Distinguished Research Scientist working on machine-learning-driven personalization and recommendations and later served as a Senior Engineering Research Manager. In that role, I led personalization science teams supporting the App Store, Apple Books, Apple Podcasts, and Apple TV.
Before joining Apple, I spent twenty-five years in higher education as a professor, researcher, and academic administrator. My last academic appointment was at Washington State University, where I served as Dean of the College of Arts and Sciences and Professor of English and Data Analytics. Earlier in my career, I held faculty and leadership positions at the University of Nebraska–Lincoln, Stanford University, and the University of Northern Colorado.
Alongside my academic and technology careers, I have been involved in several entrepreneurial ventures. I helped found three book-industry technology companies—Novel Projects, which operated as BookLamp; Archer Jockers, LLC; and Authors AI—as well as the nonprofit Western Institute of Irish Studies. I currently serve in a limited capacity as Chief Research Officer of Authors AI, where I advise on the continued development of the company’s computational methods for analyzing fiction.
My research has focused primarily on large-scale computational text analysis and the ways quantitative methods can reveal patterns in literary history and culture. That work is described most fully in my first book, Macroanalysis: Digital Methods and Literary History. Although my scholarship took a decidedly computational turn, my original training was in literary studies, with particular emphasis on Irish and Irish American literature of the late nineteenth and early twentieth centuries.
My second book, Text Analysis with R for Students of Literature, was conceived as a practical companion to Macroanalysis. In 2020, I collaborated with my former graduate student Rosamond Thalken on a substantially revised second edition, adding new chapters and updating the code to incorporate more contemporary methods and software libraries.
My third book, The Bestseller Code, coauthored with my former graduate student Jodie Archer, brought computational literary analysis to a broader trade audience. The book describes research underlying an algorithm designed to identify novels likely to appear on The New York Times bestseller list. That work received the University of Nebraska’s Breakthrough Innovation of the Year Award in 2017.