Machine learning, health, and the human questions in between.
Yinuo Zhao
Full-screen landing page with suspended letters that gently swing and react to pointer movement.
I care about
Human-Centered AI
for Health and Social Impact
I’m a master’s student in Health Data Science at Harvard University, and I received my B.S. in Computer Science with a focus on artificial intelligence from University of Toronto. My research interests lie in developing human-centered AI systems for health, environmental, and social impact applications.
My current work spans computational health, environmental modeling, and human-AI interaction. One area of my research focuses on building high-resolution air quality models for regions with limited monitoring infrastructure, including nationwide PM2.5 estimation and wildfire pollution analysis in Madagascar using deep learning and geospatial data. I am also interested in how people interact with AI systems in real-world settings. In recent work, I studied how people perceive and evaluate AI-generated well-being advice compared to human responses, with a focus on support quality, clarity, and trust. In parallel, I build interactive visualization and AI systems that help make complex data more interpretable and actionable for both experts and the public.
More broadly, I’m interested in combining machine learning, data systems, and interface design to build AI tools that are technically rigorous while remaining understandable and useful to the people they are meant to support.