Laure Thompson

As a research software engineer, Laure builds tools and creates methodologies that enable scholars to use machine learning, natural language processing, and statistical methods for studying humanities collections at scale. She collaborates with Princeton scholars on longer-term CDH-sponsored projects. She also advises and consults with the Princeton community on a wide range of computational and data-intensive projects.

Laure’s expertise is in natural language processing with particular interests in cultural analytics, interpretability, and data-centric interventions. Her research focuses on understanding what computational models actually learn and how we can intentionally change what they learn. She works with a wide range of cultural heritage corpora: from texts of science fiction novels and medieval manuscripts to images of avant-garde journals and magical gems from the ancient Mediterranean.

Before coming to Princeton, Laure was an assistant professor in the College of Computer and Information Sciences at the University of Massachusetts Amherst. She received her PhD in Computer Science from Cornell University in 2020 where she was advised by David Mimno. During her time at Cornell, she also completed a graduate minor in classical archaeology advised by Caitie Barrett.