Welcome! I am a computational linguist, specializing in theoretical phonology. My research program is focused on identifying the computational properties of phonological grammars and showing how such properties contribute to our understanding of phonological typology and learning. In particular, I demonstrate the role that computational restrictions on input-output maps play in delimiting the set of ‘possible’ phonological processes. These same restrictions also serve as inductive biases that enable efficient learning of such maps from a finite amount of positive data. This work is necessarily inter-disciplinary, combing insights and methodologies from theoretical linguistics, computer science, grammatical inference, and psycholinguistics.
My CV is available here.
Recent and Upcoming Activity
- ‘Autosegmental Input Strictly Local Functions’ (co-authored with Adam Jardine) is now published in TACL volume 7.
- “Learning with Locality Across Speech and Sign” co-authored with Jonathan Rawski presented at the Rules and Learning Strategies in the Acquisition of Signed and Spoken Phonologies workshop at GLOW 42. SLIDES
- Poster presentation at SCiL 2019: Jane Chandlee (Haverford College), Remi Eyraud (Université Aix-Marseilles), Jeffrey Heinz (Stony Brook
University), Adam Jardine (Rutgers University) and Jonathan Rawski (Stony Brook University). How the Structure of the Constraint Space Enables Learning.