Jon Rawski
Assistant Professor of Linguistics
About
I teach courses on general and computational linguistics at San Jose State University. I generally study the mathematics of human language and learning. My work places mathematical boundary conditions on the grammars underlying human language and how they can be learned. These properties reflect humans’ unique neuronal structure and computational power, contributing foundational principles for the cognitive and computer sciences.
Interests
- Mathematical Linguistics
- Cognitive Science
- Theoretical Computer Science
Recent Publications
I try to make my work accessible following the FAIR Principles, on this website or some other repository.
We characterize transformer sequence models as transducers and show some expressivity bounds for several variants.
We give a pragmatic problem-centered account of theories’ epistemic virtues, like coherence, depth, and parsimony.
The Computational Power of Harmonic Forms
We overview vowel harmony computationally, describing necessary and sufficient conditions on phonotactics, processes, and learning.
Tensor Product Representations of Regular Transductions
We give a tensor algebra characterization for regular transformations via origin graphs
Regular and Polyregular Theories of Reduplication
We show a mismatch between the generative capacity of reduplication and the theories which model it.
