Bits to Atoms
CDFAM Computational Design Symposium
Functional AI For 3D Design Automation — From Path Finding To Generative Modeling For Building Construction
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Functional AI For 3D Design Automation — From Path Finding To Generative Modeling For Building Construction

Hao (Richard) Zhang - Augmenta and Simon Fraser University

Most 3D generative AI has been built to produce things that look right. Hao (Richard) Zhang argues that for the built environment, that is the wrong objective. Buildings must function — and that means AI systems need to reason about spatial relationships, load paths, equipment routing, and regulatory constraints, not just geometry.

In this episode recorded at CDFAM Barcelona 2026, Richard introduces Functional AI as a framework for 3D design automation and walks through Augmenta’s work applying it to real building projects. The technical scope covers agentic AI for MEP path finding, generative modeling of complex structural and mechanical layouts, and progress toward a foundation model for building data. He also discusses what makes non-residential construction — commercial, medical, institutional, and mission critical — a particularly hard problem for AI systems to crack.

The conversation closes on a concrete milestone: two elementary schools in Michigan where the electrical system was fully modeled and delivered using AI-powered generative design, a first for the industry.

Hao (Richard) Zhang is VP of AI and R&D at Augmenta and a Professor in the School of Computing Science at Simon Fraser University. He is a Fellow of the IEEE, a member of the ACM SIGGRAPH Academy, and served as Technical Papers Chair for SIGGRAPH 2025.

Recorded at CDFAM Barcelona 2026 — https://cdfam.com/barcelona-2026/

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