Tom Juzek

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 and its impact on human language usage. Prior to joining FSU, Tom worked in the tech industry for several years. He also co-organizes the SC Machine Learning Seminar.

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

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).
• Juzek, T. S. (2024). Signal Smoothing and Syntactic Choices: A Critical Reflection on the UID Hypothesis. Open Mind, 8, 217-234. https://direct.mit.edu/opmi/article/doi/10.1162/opmi_a_00125/120012/Signal-Smoothing-and-Syntactic-Choices-A-Critical
• 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