IAAC’s Master in AI for Architecture & the Built Environment is a unique program oriented towards leading the change in decarbonising human activities and crafting a more sustainable, resilient future urbanisation for our planet. Through an innovative curriculum deeply rooted in AI applications, the program pioneers novel AI-driven solutions that not only respond to the pressing challenges of our time but also set a new standard for environmentally and socially conscious co-design and planning. The Master in AI for Architecture & the Built Environment is training the professionals that city administrations, governments, industries, and communities need, to transform the built environment in the era of digital technologies.


IAAC · Research Studio · 2026

GigAI: An Event-Driven Coordination Execution Layer for Construction Project Management Team: Martina Simoni · Sumit Sudhir Shingne · Rafik El KhouryFaculty: Marita Georganta & Akshay Madapura Project managers spend more than half their time chasing information that no plan ever scheduled. We built GigAI to fill that gap — the coordination execution layer that sits between planning, … Read more

Veil Of Timber

Veil of timber title

Veil of Timber explores the transformation of a parametric pavilion into a detailed, data-driven BIM system. By integrating computational design and metadata with the help of grasshopper and real-time visualisation using Speckle and Power BI. The project bridges geometry and data to enable querying, analysis, and informed decision-making. Overview The pavilion is a parametric system … Read more

Human Trace: Autonomous Single-Stroke Robotic Sketching

This project explores a robotic system that translates digital vision into physical matter through the constraint of continuity. Rather than behaving like a conventional plotter that freely lifts and re-positions its pen, the system confronts a more complex challenge: it must interpret image topology and compute a path that allows the entire drawing to be … Read more

Behavioral Investment in Urban Decision Making

PROBLEM: Current urban investment decisions, particularly in social housing, are largely based on financial feasibility studies, static socio-economic indicators, and ESG-style metrics that fail to capture how people actually experience and use space and often overlook real-time behavioral dynamics: how people move, engage with space, perceive safety, or interact socially. In dense metropolitan environments like … Read more