Q&A with Ashley Gao
“I wanted to work on something that is not only technically interesting, but also practically meaningful.”
Ashley Gao
MESc Candidate, Biomedical Engineering
What project are you working on?
I am working on a low-cost AI-assisted oral imaging project for early screening. The goal is to build an accessible imaging and analysis pipeline that can capture intra-oral images and automatically identify oral health conditions, especially in settings where dental resources are limited.
What problem(s) are you solving?
The main problem I am trying to solve is the lack of affordable and scalable oral health screening tools. In many real-world settings, especially low-resource environments, people may not have easy access to dentists or specialized imaging equipment. At the same time, oral images captured in practice often contain glare, blur, occlusion, and other noise, which makes automated analysis difficult. My research focuses on making the system both low-cost and robust, so that it can work under real-world imaging variability rather than only under ideal lab conditions.
What brought you to this research?
I was drawn to this research because it sits at the intersection of engineering, AI, and healthcare impact. I wanted to work on something that is not only technically interesting, but also practically meaningful. This project gives me the opportunity to apply computer vision and machine learning to a real health problem, while also thinking about accessibility, deployment, and how technology can be designed for use beyond highly resourced clinical settings.
