Forestry & remote sensing researcher
—
reading the forest through
lidar point clouds
I study how forests respond to disturbance at scale — fusing airborne lidar with decades of satellite imagery — and build fast geospatial tools in Rust & Python.
I am passionate about lidar and satellite remote sensing for forest disturbance characterization and monitoring. I enjoy coding in Python and Rust to develop fast processing tools that simplify the manipulation of remote-sensing data, and I am interested in deep learning and model explainability & uncertainty.
Fusing the vertical detail of lidar with the temporal depth of multi-decadal satellite records.
Forest structure in 3D
Millions of laser returns resolve a single tree or an entire forest in 3D, capturing its complext structural characteristics. I use these to understand how forests change in response to disturbances
30+ years from space
Decades of satellite imagery reveal how forests change — capturing the impact of forest fire and the recovery that follows, pixel by pixel across the landscape.
Forestry & remote sensing studies across Canada, Italy and beyond.
Tools I author and research software I contribute to.
Open to research collaborations, talks, and conversations about remote sensing, forest ecology, and fast geospatial tooling.