About

I work at the intersection of geospatial AI, applied research, and Earth observation, with a focus on turning emerging AI capabilities into practical systems and workflows.

At Esri Canada, I lead GeoAI and research initiatives spanning computer vision, geospatial foundation models, generative AI, agentic systems, spatial analytics, and machine learning for geospatial applications.

A question that runs through much of my work is simple:

What happens after the prototype?

A promising model is only the beginning. Making AI genuinely useful requires reliable data, thoughtful evaluation, reproducible workflows, integration with existing systems, clear communication, and an understanding of how people will actually use the technology.

My path into AI began with Earth observation and environmental science. I trained in geology and geomatics before moving into remote sensing, Arctic oceanography, environmental modelling, and large-scale observational data. That background still shapes how I approach AI today: the model is only one part of a larger system.

Explore Arctic fieldwork

Over the years, I have worked across industry, universities, government collaborations, and international research environments. This has given me the opportunity to move repeatedly between research, experimentation, implementation, and communication; whether developing geospatial AI workflows, contributing to environmental research, working with emerging AI technologies, or helping students and professionals understand how these methods can be applied.

I am also an Adjunct Professor in Geography at the University of Calgary, where I teach and mentor students in GIS, remote sensing, spatial data science, and applied geospatial technologies.

Today, much of my work is focused on a broader question: how AI will change the way we understand, analyze, and interact with the spatial world.