Projets de recherche

Notre laboratoire mène des recherches à travers plusieurs projets couvrant l’orthophonie computationnelle, les neurosciences et les sciences cognitives. Voici quelques-uns de nos projets actuels et récents.

Projets en cours

Abstract illustration of speech signals transforming into neural representations through artificial intelligence for developmental speech and language disorder assessment

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 language disorders.

Financement : SickKids Foundation / CIHR New Investigator Grant

Chercheur principal : Dr. Selçuk Güven

Équipe : Redha Touati (Research Scientist), Peter Pan (PhD Student)

Voice AI Multimodal Diagnosis Fairness

Conceptual visualization of probabilistic reading pathways in the brain representing computational and Bayesian models of dyslexia

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 reading outcomes in mono- and bilingual children.

Financement : SSHRC Insight Grant

Chercheur principal : Dr. Selçuk Güven

Équipe : Han Yao (PhD Student), Xinya Zhang (PhD Student)

Bayesian Modeling Dual-Route Dyslexia Bilingualism

Stylized brain illustration showing distributed neural activation patterns used for longitudinal neuroimaging of language development

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 language disorders.

Financement : Fonds de recherche du Québec – Santé (FRQS)

Chercheur principal : Dr. Selçuk Güven

Équipe : Farhan Jahan (PhD Student)

Bilingualism fNIRS Longitudinal Language Disorders

Illustration of a feedback loop between clinician, child, and artificial intelligence representing reinforcement learning for personalized speech-language therapy

Reinforcement Learning (RL) for Individualized Speech–Language Therapy

Building reinforcement-learning decision-support tools embedded in clinician workflows to personalize and optimize speech–language therapy while preserving clinician oversight.

Financement : Brain Canada – Future Leaders of Brain Research Grant

Chercheur principal : Dr. Selçuk Güven

Équipe : Lorna McGregor Smith (PhD Student)

Reinforcement Learning Clinical Decision Support Speech-Language Therapy Personalization

Ressources des projets

Données & Code

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Opportunités de collaboration

Nous accueillons volontiers des collaborations autour de ces projets et de thématiques connexes. Si vous êtes intéressé·e :

Consultez notre page Recherche
Contactez le responsable du projet concerné
Ou utilisez notre formulaire de contact

Participation des étudiant·e·s

Étudiant·e·s au baccalauréat : postes d’assistant·e de recherche, stages d’été
Étudiant·e·s à la maîtrise : projets de mémoire, stages de recherche
Doctorant·e·s : projets de thèse, implication à long terme

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