I combine data analysis and user research to understand how people use, trust, and make sense of technology, with work across human-centred data science, product analytics, and human–AI interaction.
At a glance
Previously
Research Sciences Intern, Human-Centred Design @ TD
NLP Research Intern @ University of Waterloo
Education
M.I. — Human-Centred Data Science
🏙️ University of Toronto · Part-time · 2026–2029 (expected)
B.Sc. — Computational Intelligence and Design
🏔️ University of British Columbia · Graduated 2026
Co-authored and co-presented research on voice-based AI assistance for older adults at the BC AI Research-to-Adoption Summit 2026. Read the protected case study →
TD
Co-developed four evidence-based NACO personas from 10,000+ feedback records, call review, and frontline research; also supported CX reporting and online discourse research on AI-assisted investing.
View project >
UBC eDAPT Research Group
Researched, designed, and evaluated multimodal voice interactions to make online banking more accessible for older adults. Manuscript under peer review.
View protected case study >
Global Relay
Combined behavioral data, surveys, interviews, and usability findings to clarify enterprise communication workflows.
View protected case study >My previous research spans human–AI interaction and NLP: I have studied how older adults use and trust voice-based AI support, as well as language and cultural knowledge through computational methods. I also volunteer with communities that expand access to AI education, ethics and governance, tech and research pathways, and design support for nonprofits.
I try to hold curiosity and discipline together: asking better questions, staying honest about uncertainty, and changing course when the evidence challenges an assumption. Even when systems and data are complex, I want the work to stay grounded in the people who actually use them. I aim to be rigorous without being slow, creative without guessing, and pragmatic enough to produce useful answers within real constraints.
