During the second year of the Master in AI for Architecture & the Built Environment students have the opportunity of working hand in hand with a series of renowned experts and industry partners in various fields, to develop an in-depth individual research agenda. Students propose a thesis project, to be developed throughout the year, and are allocated with an Individual Thesis Advisor, Technical Advisor, Business Development and Industry Advisor. During the second year of the program, the curriculum of the program gives students the chance to either participate in an accelerator program or embark on a paid internship with renowned architectural and urban design offices around the world that collaborate with the programme. This experience enables students to apply their newfound expertise in real-world settings, contributing to impactful projects, establishing strong future career possibilities and expanding their professional networks.
Reading City Morphologies This project is situated in an urban district selected via bounding box coordinates using satellite data (Google Earth Engine).The research aims to analyze how building footprints evolve over time using satellite imagery and segmentation techniques.We applied temporal image extraction (multi-decade), followed by image segmentation to detect and outline changes in urban fabric.Key … Read more
Abstract: Natural disasters, especially earthquakes, often leave roads blocked, buildings collapsed, and maps outdated, making navigation and response efforts highly challenging, That’s where we operate. Our project SeisNAV is an AI-powered platform that combines satellite imagery and computer vision to detect collapsed structures and road blockages, providing real-time mapping and navigation tools for disaster response … Read more
Abstract:Emergency response planning is a vital aspect of urban resilience, requiring precise decisions on resource allocation and infrastructure placement. In our research, we explored how data-driven tools can optimize emergency response times using geospatial analysis and computational design methods. Focusing on Kadikoy district in Istanbul, we simulated ambulance routes from stations to emergencies and onwards … Read more
Abstract: In this class on Intelligent Prototyping within the MaAI program, we explored two distinct approaches to prototyping: 3D printing with robotic arms and real-time sensing with microcontrollers. Using parametric modeling tools, specifically Grasshopper, we designed and fabricated a series of 3D-printed clay pots. These included small, medium, and large-scale pots, with a focus on … Read more
Introduction:The AI Theory class has provided us with comprehensive foundation in artificial intelligence, covering both fundamental principles and advanced methods. Through topics such as clustering, neural networks, evolutionary computing, and decision-making models, the course aims to equip students with the theoretical knowledge and practical insights needed to apply AI across various fields, including disaster management … Read more
