Areas of Focus

Human-Centered AI

I believe the most important question in AI is not what a system can do, but how it affects the people using it. My interest in human-centered AI comes from previously studying user interfaces, human-computer interaction, and cognitive psychology. I care about building systems that are not only capable but legible, where users can form accurate mental models of what the system is doing and why.

In practice, this often means making deliberate tradeoffs: prioritizing transparency over raw performance, constraining model behaviour to reduce ambiguity, and designing interfaces that reflect real cognitive limits rather than idealized users. I am also increasingly conscious of the environmental cost of the systems that power these models and how that should influence when and how they are used.

Geospatial Systems

I have deep secondary interests in cities and the natural environment, and I find it most rewarding to build software that engages with the physical world - tools that ask real questions about how urban spaces change over time and who bears the cost of those changes.

I’m currently building Drift, a urban change dashboard for Toronto, and Mealer, a map-based restaurant tracker and recommender web app. Both projects reflect the same core interest of supporting better interaction and planning in my own city.

Secure, Private Data Science

Data at scale creates real risk for individuals and communities. My background in machine learning, security, and cryptography has led me to think about privacy as a systems problem rather than a feature.

I am interested in how data is collected, transformed, stored, and exposed - and how decisions at each stage affect what can be inferred about individuals and communities. Just because something is technically possible doesn’t mean that collecting and using the data was justified to begin with.