LabCompass

Julia Taylor Rayz

Computer Science · Purdue University West Lafayette

Mid career · publishing since 2016

Publications

89

Citations

302

Est. group size

~3

Recurring co-author estimate

Active years

11

Publishing since 2016

Research summary
AI-generated

Julia Taylor Rayz works in computational linguistics and natural language processing, studying how computer models understand meaning, concepts, and language structure. Her work examines whether language models (such as those behind chatbots) can learn human-like knowledge about word meanings, categories, typical properties of objects, time, and even emotional content like sentiment or emojis. She also applies these techniques to practical problems such as detecting phishing emails, stereotypes in news, and misspellings.

Natural language processing and language modelsMeaning and concept representation in AIText analysis (sentiment, stereotypes, topic tracking)Language model evaluation and knowledge testingApplications: phishing detection, misspelling correction, social media analysis

Publication output rose notably around 2020-2021 and has since settled back to a more moderate, steady pace in recent years.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 6.8/year recently
2017: 6 publications172018: 5 publications182019: 9 publications192020: 11 publications202021: 21 publications21212022: 11 publications222023: 6 publications232024: 8 publications242025: 7 publications252026: 2 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×25
  • Proceedings of the ... International Florida Artificial Intelligence Research Society Conference×5
  • Lecture notes in networks and systems×4
  • Advances in intelligent systems and computing×3
  • Zenodo (CERN European Organization for Nuclear Research)×2
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  • Weixuan Wang

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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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