Tom Juzek

Assistant Professor
Tom Juzek

Contact Information

Office Location
DIF 304A, DSL/SC 479
Email
tjuzek@fsu.edu
Phone
850-644-3727
Program
Linguistics
Office Hours

ann. in class, and by appt.

Tom Juzek (M.A. phonetics, University of Bonn; Ph.D. linguistics, Oxford University) is an assistant professor of computational linguistics, with a courtesy appointment in Scientific Computing. His research interests include the application of computational methods to linguistic questions, with a current focus on the features of AI-generated language, its impact on human language usage, and the causes that influence model behavior. Prior to joining FSU, Dr Juzek worked in the tech industry for several years. He also co-organizes the SC Machine Learning Seminar.

In the news: Dr Juzek’s work has been featured in national media outlets such as Science Friday, picked up by the international press (Die Welt; paywall), and covered in a long-form conversation on the Tallahassee-rooted podcast Ask a Scientist Gaming.

Mentorship: Dr Juzek serves as the advisor for the Computational Linguistics track in FSU's Data Science Program. He also mentors several students participating in the Undergraduate Research Opportunity Program (UPOP). If you have any questions or are interested in researching language and AI, feel free to reach out.

Research Interests

  • Computational linguistics
  • Natural language processing
  • Corpus linguistics
  • Experimental and information theoretic approaches

Courses Taught (selection)

  • LIN3041: Introduction to linguistics I
  • LIN3042: Introduction to linguistics II
  • LIN3771: AI-assisted Python programming for language data
  • LIN5932: Topics in linguistics - research methods

Selected Publications

  • Juzek, T. S., & Ward, Z. B. (2025). Why Does ChatGPT “Delve” So Much? Exploring the Sources of Lexical Overrepresentation in Large Language Models. The Proceedings of the 31st International Conference on Computational Linguistics (COLING 2025). https://aclanthology.org/2025.coling-main.426/
  • Juzek, T. S. (2024). Signal Smoothing and Syntactic Choices: A Critical Reflection on the UID Hypothesis. Open Mind, 8, 217-234. Full article.
  • Juzek, T. S., Krielke, M. P., & Teich, E. (2020). Exploring diachronic syntactic shifts with dependency length: the case of scientific English. In Proceedings of the Fourth Workshop on Universal Dependencies (UDW 2020) (pp. 109-119). https://aclanthology.org/2020.udw-1.13.pdf

More publications at Google Scholar.