Cognition, Oral & Written Language Disorders, and AI Laboratory
Advancing earlier, fairer, and clinically meaningful assessment and support for children with speech, language, and reading-writing difficulties.
COALab is an interdisciplinary research laboratory dedicated to understanding and supporting children with speech, language, and reading difficulties. Our work sits at the intersection of speech-language pathology, developmental neuroscience, and artificial intelligence, with a shared goal of improving how language disorders are identified, understood, and treated—earlier, more fairly, and more effectively.
At COALab, we combine behavioral assessment, brain-based measures, and computational modeling to better capture individual differences in speech, language and reading-writing development and to translate scientific insight into clinically meaningful tools.
Latest Highlights
View All NewsNew PhD Students Join COALAB
COALAB welcomes new doctoral trainees spanning neuroscience, speech-language pathology, and computational modeling.
Read more →SSHRC Insight Grant Awarded
Funding to advance computational approaches to reading development and dyslexia in bilinguals.
Read more →Brain Canada Future Leaders Grant
Support for reinforcement-learning approaches to individualized pediatric speech-language therapy.
Read more →Research Areas
Oral & Written Language Disorders
We study speech, language, and reading-writing difficulties across development, with a focus on characterizing individual profiles and improving clinical assessment and intervention—especially in diverse and bilingual contexts.
Learn MoreArtificial Intelligence
We develop voice-based AI and computational models to support screening, diagnosis, and prognosis of neurodevelopmental disorders, with a strong emphasis on interpretability, fairness, and real-world clinical relevance.
Learn MoreDevelopmental Neuroscience
Using child-friendly neuroimaging (e.g., fNIRS), we examine the neural systems supporting language, working memory, and cognitive control, and how these trajectories differ in children with language disorders.
Learn MoreFeatured Projects
AI-Driven Multimodal Diagnosis of Developmental Speech and Language Disorders (DSLD)
Developing a multimodal voice-AI diagnostic pipeline to enable earlier, fairer, and more objective identification of developmental speech and langu...
Bayesian and Computational Modeling of Dyslexia in Mono- and Bilingual Children
Using Bayesian modeling and dual-route computational frameworks to refine dyslexia subtyping, capture cross-linguistic variability, and predict rea...
Early Identification and Longitudinal Tracking of Language Disorders in Bilingual Children Using Neuroimaging
Longitudinal tracking of bilingual children using child-friendly neuroimaging and behavioral measures to identify early markers and trajectories of...
COALAB — Cognition, Oral & Written Language Disorders, and AI