Geospatial AI for beluga whale detection
Supported deep learning work with Fisheries and Oceans Canada to detect beluga whales in Arctic imagery from aerial surveys, drones, and satellites, helping distinguish whales from sea ice and whitecaps.
Location: 51.050° N - 114.085° W
I'm My professional roles include Geospatial AI & Research Lead, Lead Data Scientist, Adjunct Professor, Oceanographer, Geospatial Nerd.
I work at the intersection of spatial data, Earth observation, and applied AI. My path has taken me from geoscience and Arctic oceanography to building production GeoAI systems, and along the way I learned that the hardest part of AI is rarely the model itself. It is the quality of the data, context, and infrastructure that determines whether AI becomes genuinely useful. Today, I build GeoAI tools and workflows for research, government, and industry, and I still love just about anything involving maps.
Supported deep learning work with Fisheries and Oceans Canada to detect beluga whales in Arctic imagery from aerial surveys, drones, and satellites, helping distinguish whales from sea ice and whitecaps.
Contributed as a co-author to Canada's Oceans Now: Arctic Ecosystems 2023, with focus on CO2 cycling, ocean acidification, and how Arctic waters can act as seasonal sources or sinks of atmospheric carbon dioxide.
Built an interactive treemap visualizer mapping AI exposure, job outlook, and education requirements across 516 Canadian occupations from ESDC Job Bank NOC data, covering roughly 20 million jobs.
Packaged Canadian geospatial foundation models for ArcGIS Pro change detection workflows, enabling before-and-after satellite imagery analysis with HLS and Sentinel-2 variants.
Designing agentic workflows that help teams discover, run, explain, and scale geospatial analysis.
Packaged Meta's SAM 3.1 model into an ArcGIS-ready deep learning workflow for object tracking, bringing foundation-model segmentation into practical GIS analysis.
Turning satellite, aerial, drone, and environmental data into applied AI systems for detection, segmentation, classification, change analysis, and environmental monitoring.
Taking AI beyond the prototype by integrating models and intelligent workflows into GIS systems that are reproducible, explainable, scalable, and ready for operational use.
Designing AI assistants and agentic workflows that can discover information, reason over spatial context, use geospatial tools, automate analysis, and support better decisions.
Leading applied research and translating emerging AI methods into practical technology, strategy, guidance, and learning across industry, government, and academia.
Technologies I use to move from geospatial data and AI research to deployable applications and operational workflows.
2026-08-10 · Change Detection with Planaura in ArcGIS
2026-07-08 · Teaching and Learning GIS in the Age of AI (Part 2 of 3)
Contact
Interested in GeoAI, applied research, teaching, or spatial AI workflows? Please reach out to discuss potential collaborations, research, or consulting opportunities.
DM on LinkedIn