Architectural Fashion: AI & 3D Printing

This workshop explores how digital workflows can bridge the conceptual world of architecture with the expressive, material-focused domain of fashion. Over two days, the course takes a deep dive into the fusion of computational design, artificial intelligence, and digital fabrication to develop wearable structures that move beyond traditional fashion norms.

We begin by looking at how reaction-diffusion systems, patterns found in nature, can be used as design tools. Starting in Grasshopper, we’ll simulate these organic patterns using pre-written Python scripts that students can modify without prior coding experience.

These simulations act as the digital DNA of the Metal Dress, a wearable prototype born from algorithmic growth and realized through digital fabrication techniques.

The digital workflow continues with a look into the practicalities of production. Students are introduced to fabrication methods for both metal and 3D-printed textiles, learning about material constraints, equipment settings, and post-processing techniques. 

On Day 2, the focus shifts to the 3D-Printed Dress, a modular, rippling structure built using fractals and custom G-code.

Students will see how customized toolpaths can be used to break open the traditional 3D printing pipeline and expose creative opportunities often overlooked.

We then pivot to artificial intelligence tools like Midjourney and Stable Diffusion, using them to generate conceptual imagery. These AI-generated visuals are not just mood boards, they become design data.

This workshop will teach you how to extract vector geometries from AI outputs, transforming them into NURBS-based structures ready for fabrication.

Students are encouraged to experiment, remix, and question each stage of the process. Whether producing intricate wearable sculptures or rethinking how AI can shape material aesthetics, the workshop invites participants to challenge the limits of what fashion can be when architecture, algorithms, and fabrication collide.