Research Projects

Our lab conducts research across multiple projects that span computational speech-language pathology, neuroscience, and cognitive science. Below are some of our current and recent projects.

Active Projects

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.

Funding: SickKids Foundation / CIHR New Investigator Grant

PI: Dr. Selçuk Güven

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

Voice AI Multimodal Diagnosis Fairness
Read More
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.

Funding: SSHRC Insight Grant

PI: Dr. Selçuk Güven

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

Bayesian Modeling Dual-Route Dyslexia Bilingualism
Read More
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.

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

PI: Dr. Selçuk Güven

Team: Farhan Jahan (PhD Student)

Bilingualism fNIRS Longitudinal Language Disorders
Read More
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.

Funding: Brain Canada – Future Leaders of Brain Research Grant

PI: Dr. Selçuk Güven

Team: Lorna McGregor Smith (PhD Student)

Reinforcement Learning Clinical Decision Support Speech-Language Therapy Personalization
Read More

Project Resources

Data & Code

We believe in open science. Where possible, we make our data and code publicly available:

Collaboration Opportunities

We welcome collaborations on these and related projects. If you're interested:

  1. Review our Research page
  2. Contact the relevant project lead
  3. Or use our general contact form

Student Involvement

For joining the lab, see our Contact & Join page.