The funded cohort brings together from around the world working across anxiety, depression and psychosis. Projects span digital mental health, clinical decision support, conversational AI, implementation science, evaluation, measurement, and culturally adapted interventions.
Together, the cohort represents a diverse portfolio of approaches aimed at advancing the responsible development and application of generative AI in mental health.
SYLFAEN-PSY: SYmptom Learning through Foundation models to Augment and ENhance measurement in PSYchosis
shamiriAI – Scalable, Culturally-Informed AI for Fidelity Feedback and Adaptive Training in Youth Mental Health
ARIADNE: ARtificial Intelligence-based Assessment to Detect iNdividuals with Emerging psychosis risk
Baylor College of Medicine
AURORA: Adaptive Understanding through Real-time Observation, Reporting, and Assistance
Slum and Rural Health Initiative
GENSCORE Project: Leveraging Generative AI to adapt and enhance the scoring of widely used mental health assessment tools in low-resource context
AI4You(th): Advancing Generative AI for Personalised and Collaborative Youth Mental Health Care
HAI-Team: Human–AI Teaming Therapeutic Companion for Torture Survivors with PTSD
STELLAR – Steering-Vector Enhanced LLM Agents for Realistic Digital Twins in Mental Health
Julia R Pozuelo / Vikram Patel
Bridging the Treatment Gap with AI-Enhanced Supervision (BRIDGE-AI)
The Children’s Hospital of Philadelphia
Generative AI for Identifying Mechanisms and Intervention Points in the Intergenerational Transmission of Anxiety
National Institute of Mental Health and Neuro Sciences
Human-in-the-loop Evaluation of Assisted Depression Screening (HEADS)
Generative AI for Simulated Conversations: Preparing Frontline Workers and Volunteers to Support Youth with Anxiety and Depression
Culturally Aligned Generative AI to Support Para-Counselors in Low-Resource Mental Health Settings
African Population & Health Research Centre
FarajaMH: Culturally Adapted Generative AI Model for Mental Health Screening in Kenya and Tanzania; Leveraging Longitudinal Data, Clinical Notes and Conversational Chats