The MaCAD is a unique online programme training a new generation of architects, engineers and designers ready to develop skills into the latest softwares, computational tools, BIM technologies and AI towards innovation for the Architecture, Engineering and Construction (AEC) industry.
KIFAF TOWERS-Graph Machine Learning
Can graph machine learning read a real, complex high-rise the way it reads a clean dataset? We try to both, understand how the building works as a circulation network, and predict what each room is from layout structure alone THE DATA SET The dataset and the schema — the benchmark we force our tower into. … Read more
Designing for Encounter: How Spatial Analysis Reveals the Social Potential of Circulation Spaces
Introduction When we imagine a corridor in a typical apartment building, we picture a purely functional passageway — a space designed for movement, not for meeting. These circulation zones are often long, narrow, and socially inert. Yet they structure much of our daily experience of housing, shaping how residents encounter one another. Cohousing projects show … Read more
Habitar 7.2 as a Graph
Habitar 7.2: Graph Machine Learning of an Architectural Floor Plan Habitar 7.2, a residential building by Giancarlo Mazzanti and Alejandro Castaño in Bogotá, was used as a case study to test how an architectural floor plan can be translated into a graph, analysed through spatial intelligence, and classified room-by-room with a graph neural network. The … Read more
Brownstones
For the Graph Machine Learning (ML) seminar we took a classic New York brownstone and asked how graph ML can read the way a building is organized, and what happens when that organization changes. Objective: Our goal was to model an old and a new brownstone layout as spatial graphs in TopologicPy, compare how the … Read more
Decoding Architecture with AI: Graph Machine Learning at The Interlace
Have you ever looked at a complex building and wondered how a machine might understand its layout? In a fascinating project from IAAC MaCAD, researchers built a graph-based analysis and learning pipeline to decode architectural floor plans. Using “The Interlace” in Singapore as their primary case study, the team demonstrated how converting floor plans into … Read more
Analyzing Narkomfin Through Its Graph
The building The Narkomfin Building was completed in 1930 in Moscow, designed by Moisei Ginzburg and Ignaty Milinis. It is one of the most recognized examples of Soviet Constructivist housing — a dom-kommuna, or communal house. The design was deliberately unconventional: kitchens were minimal because residents were expected to eat in a shared canteen, and living … Read more
La cité Radieuse
How does the spatial organization of Unité d’Habitation influence circulation, accessibility, and apartment connectivity, and can machine learning predict room functions from graph properties? Floor plans: Spatial Intelligence 3 floors study One floor Study One Apartment Study Graph Machine Learning s Graph Machine Learning
