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.
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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
- Museum Daylight Design 2026: Bloch 200 Lux vs Generative Redesign September 9, 2026
- Chicago Logan Arts Center: 474-Seat Hall vs 150-Person Cutoff 2026 September 6, 2026
- 2026 10ft vs 13ft Height: 30ft Pass, 39ft Fail FAR Cost September 4, 2026
- Broad Veil: 650 Tons for 44.8% Daylight, 480 vs 900 Tons September 2, 2026
- Breuer Building: Four Tenants in 60 Years Make the Case for Reuse September 1, 2026
- Amazon Helix: How Parametric Massing Shaped HQ2's Spiral August 30, 2026
- Finch3D vs. Autodesk Forma: A 12-Minute Decision, Not a Race August 29, 2026
- Forma vs. Grasshopper-Wallacei: Speed, Accuracy, Trade-offs August 27, 2026