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.


Agrowealth : Does agriculture correlate to economy?

The goal of this project is to compare between the economic stability of an agriculture first city. Hamburg’s agricultural wealth is largely connected to its surrounding regions—particularly Schleswig-Holstein and Lower Saxony, which are among Germany’s leading food producers. Consequently, we focused on peripheral areas of the city that have recently transitioned into agricultural land, allowing … Read more

GG WORLDS [v.01]

GenAI for Game Environment Creation OverviewUrban environments in games play a crucial role in crafting immersive, dynamic worlds that captivate players and enhance storytelling. These settings not only shape the game’s atmosphere but also introduce strategic challenges and reflect cultural, social, and architectural identities, making virtual spaces feel authentic. However, creating high-quality, realistic game environments … Read more

Real time fabrication space control

AI for Robotic Fabrication Real-time control in fabrication spaces is essential for enhancing operational efficiency, minimizing risks, and ensuring worker safety. In dynamic manufacturing environments, accurately locating and tracking elements—such as machinery, tools, materials, and personnel—can drastically reduce accidents, optimize workflows, and streamline resource management. Through this project, we aim to integrate advanced sensing technologies, … Read more

AI For Robotic Fabrication Workshop : Reinforcement Learning for Intelligent Grid-Based Carving

Can an AI agent learn how to carve a shape — not by following a predefined path, but by figuring it out on its own? https://github.com/IaaC/AI_Robotics_Octopus.git Inspired by the precision of traditional craftsmanship, especially techniques like Japanese joinery where every cut matters, we wanted to see if a machine could learn that same logic in … Read more

AI FOR ROBOTIC FABRICATION: Smarter Motion by Bridging Simulation and Reality in Robotic Clay 3D Printing

https://github.com/PaintDumpster/ai_for_robotic_fabrication.git In the field of robotic fabrication, precision is everything! Yet there’s often a significant gap between a simulated toolpath and the real-world movement of a robotic arm. Subtle discrepancies can lead to printing errors, structural issues, or failed prototypes. We explored how AI can be used to minimize this gap. This investigation sits at … Read more

Reinforcement Learning for Robotic Pick and Place

In pick-and-place robotics, a robotic arm must move from a start position to a target location (e.g., to pick or place an object) while safely navigating around obstacles. These obstacles may vary in size, severity, or risk — requiring the robot to adapt its path based on the workspace condition. This project simulates the core … Read more