Before I knew what GIS was, I was spending hours with road atlases —
tracing how routes connected cities, how rivers shaped where borders fell,
how the geography of a place explained almost everything else about it.
When I took my first GIS course in college using ArcMap, the connection was
immediate: this was the discipline of turning geographic questions into
decision-support systems — spatial tools that help organizations understand risk,
plan infrastructure, and act on geographic data.
I've worked on problems across defense, conservation, international development,
and civic tech — and what ties them together isn't the domain, it's the approach.
Understand who the map is for. Get the data right before opening the software.
Notice what's broken before it becomes someone else's problem.
I want to work on spatial problems that matter — whether that's environmental analysis,
infrastructure planning, transportation networks, or enterprise database workflows — with teams that take data seriously.
Some of my most important work I can't show here — three maps for the Armenian
Virtual College covering infrastructure corridors in a geopolitically sensitive region.
That data didn't exist publicly. It had to be hand-digitized from imagery, georeferenced,
and spatially validated before it could be mapped at all. That kind of rigor
is what I bring to every project, whether or not the stakes are classified.
Since 2024, I've focused on deepening expertise in raster analysis, remote sensing,
and GeoAI — while also building toward enterprise GIS competencies in spatial databases,
SQL, PostgreSQL/PostGIS, and network analysis. I've completed advanced Esri and Udemy
certifications in Python-based GIS and agentic spatial systems, and stay actively engaged
through CalGPN and BayGeo. The technical depth keeps expanding. The curiosity that started
with road atlases never stopped.
