Savannah Jenkins
Editor at agustin-otegui.com
Savannah Jenkins is a PhD candidate in Computational Architecture at MIT, where her research focuses on generative design algorithms and AI-driven architectural optimization. She investigates how machine learning can accelerate early-stage building design, from floor plan synthesis to structural performance feedback. Deep experience. Intellectual curiosity.
Editorial standards
Our editorial standards are built on an unwavering commitment to accuracy, independence, and integrity: every piece of content is rigorously fact-checked against primary sources, subjected to multiple layers of editorial review, and held to the highest standards of clarity, fairness, and transparency, ensuring that readers receive trustworthy, well-reasoned information free from bias, conflicts of interest, or sensationalism.
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Recent articles by Savannah Jenkins
- Choose 2026 Crowd Flow Threshold: Independence Square 30,000-Person Limit vs Capacity October 19, 2026
- Generative vs manual floor plans 2026: run a 10-iteration time trial October 16, 2026
- Generative Design Cuts Timber 32% on a Public Garden Treehouse Platform October 13, 2026
- Krallerhof ATMOSPHERE Spa: Verify Access, Ceiling, and Terms Before You Book October 9, 2026
- Building Energy Modeling 2026: Zaha Hadid Generative Design 60% Cut vs Manual Still Wins October 6, 2026
- National Holocaust Monument: 2,711 Stelae—Visit or Skip? October 3, 2026
- Daylight Massing Test: Spatial Daylight Autonomy (300/50%)/Annual Sunlight Exposure—Pick C September 30, 2026
- Hospital Window Shade Design: 55% vs 22% Open-Weave Pick for Queensland September 27, 2026