Research
My research focuses on sociolinguistic variation and the application of computational and corpus-linguistic methods to the study of patterns in human language. I am particularly interested in how large-scale linguistic data can help us better understand language variation as well as morphology and syntax.
Research Areas
Greek Dialectology & Sociolinguistics
My thesis research examines morphosyntactic variation in the past tense among first generation Greek speakers in Canada. This work explores how linguistic features are maintained and adapted in diaspora communities and contributes to our understanding of language variation.
Computational and Corpus Linguistics
I am interested in the use of computational tools and corpus-based methods to analyze large-scale linguistic datasets. These methods allow researchers to identify patterns of variation and structure that may not be visible in smaller or manually analyzed datasets. This is especially relevant for work in morphology and syntax where we often need large datasets to find enough variable contexts to analyze patterns of variation effectively.
Projects
Morphosyntactic Variation in the Past Tense of Greek Canadians
MA Thesis, Simon Fraser University
This project investigates variation in past tense morphology among Greek heritage speakers in Canada. The research explores how morphosyntactic features are distributed across different dialects and social groups within the Greek-Canadian community, contributing to our understanding of language and especially morphological variation across Greek dialects.
Register Variation in Podcasts
LING 803 class project under Dr. Maite Taboada
This project examined register variation across podcast genres using computational linguistic methods. The work was conducted as part of the LING 803 seminar at Simon Fraser University and resulted in a publication in the Register Studies Journal.
Greek Forced Alignment Pipeline
Computational Linguistics Project
I am currently working on revising and improving the Greek forced alignment pipeline built around the Montreal Forced Aligner (MFA). The goal of this work is to make the pipeline more accessible and user-friendly for researchers working with Greek linguistic data. I am also updating the Greek models that I trained to ensure higher accuracy and lower OOV word rates for Greek data.