Kyle Mahowald

Kyle Mahowald serves as an Assistant Professor in the Department of Linguistics at the University of Texas at Austin. His work bridges computational linguistics, machine learning, and cognitive science, focusing on extracting insights about human language from large language models and exploring information-theoretic explanations for linguistic variation across languages.

• Education: M.Phil in Linguistics (University of Oxford), Ph.D. in Cognitive Science (Massachusetts Institute of Technology), Postdoctoral Researcher in the Stanford Natural Language Processing Group.

His research investigates the distinction between formal linguistic competence (rule-based knowledge) and functional competence (practical language use in real-world contexts), with implications for understanding both human cognition and AI capabilities. He actively contributes to interdisciplinary studies through publications in venues like ACL, EMNLP, NeurIPS, and Cognition.

Awards include the Outstanding Paper Award at EMNLP and the National Science Foundation's CAREER grant, reflecting his impact in computational linguistics and cognitive science. Kyle participates in the "Using Language Models for Linguistics" session at the 2024 ISC Summer School, where he will discuss the scientific and ethical dimensions of large language models.