A passionate team of undergraduate students committed to leveraging technology for social good.
A passionate team of undergraduate students committed to leveraging technology for social good.
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🌟 Background
🌟 Background
We are students who recognized the gap in accessible, personalized menopause support and decided to take action.
Vision: Harnessing artificial intelligence to create positive social impact and address real-world challenges.
Focus Areas:
Healthcare accessibility
Social equity through technology
Community-driven solutions
Responsible AI development
Lab Mission: To develop AI solutions that improve lives, reduce barriers to essential services, and create more inclusive communities.
Our Role: As student researchers in AI4Good Lab, we combine technical skills with social awareness to build meaningful solutions.
Team Demonstration at AI4Good Lab
🎯 Our Mission: Building Thalia
🎯 Our Mission: Building Thalia
The Problem We're Solving:
1.3 billion women worldwide will experience menopause by 2030
Limited access to specialized menopause care
Stigma and lack of open discussion around menopause
Fragmented information and support resources
Our Solution: Thalia is an AI-powered conversational assistant designed to provide personalized, accessible, and confidential menopause support 24/7.
Why "Thalia"? Named after the Greek muse of flourishing and abundance, representing our vision of helping women thrive during their menopause journey.
Core Values:
Accessibility: Available anytime, anywhere
Privacy: Confidential and secure conversations
Empowerment: Evidence-based information and support
Inclusivity: Culturally sensitive and multilingual support
Meet the team
Meet the team
Sabia Irfan
Background: Bachelor of Science in Computer Science and a Math minor, McGill University
Contribution: Planned privacy feature implementation and compiled research papers for the database
Contact: https://www.linkedin.com/in/sabiairfan/
Eva Lin
Background: Bachelor of Arts in Computer Science and Statistics, McGill University
Contribution: Designed & implemented the symptom assessment flow (backend pipeline), developed the chatbot interface (frontend), and led prompt engineering for dynamic response generation.
Contact: evalin2951@gmail.com
KK Jieqi Luo
Background: Bachelor of Science in Computer Science and Biology, McGill University
Contribution: Developed RAG pipeline backend, full-stack disclaimer and login functionality, project management.
Contact: jieqi.luo@mail.mcgill.ca
Paria Jafarian
Background: Bachelor of Engineering in Software Engineering, Concordia University
Contribution: Developed and presented the pitch for Thalia.
Contact: www.linkedin.com/in/paria-jafarian
Ameline Ramesan
Background: Bachelor of Arts in Computer Science, McGill University
Contribution: = Designed and implemented the database architecture to ensure efficient data storage, scalability, and streamlined data retrieval. Worked closely with teammates to connect external pipelines to the database, and pitched at AI4GoodLab.
Contact: email: ameline.ramesan@icloud.com
Qi Zeng
Background: Bachelor of Arts in Computer Science and Mathematics, McGill University
Contribution: Developed the prompt features and contributed the symptom assessment flow
Contact: qi.zeng@mail.mcgill.ca
Mentors
Mentors
Karla Felix
AI4Good Lab Mentor
🙏 Acknowledgments
🙏 Acknowledgments
We thank AI4Good Lab for providing the platform and support for this meaningful project. Special recognition to our mentors, advisors, and the women who shared their experiences to help us build a better solution.
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