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.
In this seminar, you will be introduced to conceptual perspectives around dataset design, feature encoding, for targeted ML applications. You will develop your own ML pipeline for a use case of your choice taking departure from a common building-specific dataset.
view Syllabus & Faculty
Building a Production-Ready Property Valuation Model In the landscape of urban development, real estate investment, and computational design, accurate property valuation is essential. Yet, the datasets we rely on are rarely clean, tidy, or immediately ready for predictive use. This blog post unpacks how our team developed a robust, interpretable machine learning model for property … Read more
Bridging Carbon estimations in early design stages The built environment accounts for nearly 40% of global carbon emissions, the urgency to integrate sustainability into architectural and engineering processes has never been greater. Yet, decisions made in the earliest stages of building design often lock in the majority of a structure’s lifetime carbon footprint, long before … Read more
1 — Project OverviewOur project is based on the building geometry model that is provided with three apartment types and spaces in between them. We chose to focus on the shared spaces: the courtyards, terraces, and balconies. The building is located in Barcelona, so we rely on fixed environmental conditions and don’t re-run simulations. We … Read more
Fire Spread Prediction in Building Layouts Project Goal The goal is to predict fire safety risk at the unit level in a building. We are conducting a fire spread analysis for building layouts by examining spatial, structural, and material features. The objective is to model and understand how fire propagates through different parts of a … Read more
