Architectural Designer & Applied ML Engineer
Bridging the gap between high-dimensional data and the built environment.
I am building tools that help designers navigate the landscape of architectural style and visual semantics. My work focuses on Manifold Learning (UMAP/HDBSCAN) and Multimodal AI to create new ways of seeing the architectural market.
🚀 Featured Project: MorphoMap
The Architectural Manifold Engine. A production-grade pipeline that projects 1536D visual project embeddings into a stable 2D semantic galaxy, grounded in the Pritzker Laureate corpus.
Beyond spatial analytics, I have extensive experience building and deploying autonomous AI agents. I specialize in containerizing ML workflows to ensure scalable, production-ready inference.
- Infrastructure: Certified in taking models from "Local Script" to "Cloud Service" using Docker, AWS, and Google Cloud Run.
- Deployment: Architecting CI/CD pipelines for containerized AI environments.
- AI/ML: Python, UMAP, HDBSCAN, Scikit-Learn, Gemini Multimodal Embeddings, Agentic Frameworks
- Cloud & DevOps: Docker, AWS, Google Cloud Platform (GCP), Cloud Run
- Design Tech: Next.js, Deck.GL, React, D3.js, Supabase
- Architecture: Computational Design, Spatial Semantics, Urban Analytics
- SoftMarket: Live Visualization
"I believe the future of design isn't just about form—it's about how we map the meaning behind it."