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Research Project

Made In Damascus
My Personal City

Made in Damascus looks into the material of the city in multiple scales, and turn it into an innovative way of participatory design which can be applied to post-conflict region such as Zamalka as an example. The project starting from looking at the static city and focusing on balcony as the essential static element of Damascus that represents private and public as well as shapes the city’s social-cultural identity. The potential of the material in Zamalka that can be repurposed and reprogram into the city. How do we design a public balcony that both represent the form and facade of the building in terms of its residents and the city altogether? How the act of the design and build of balcony together could potentially design the new region?

By using machine-learning-driven image segmentation and data mining of street images, the project manages to connect a subjective selection of objects and the city context in detail. The personally selected objects can be trained in the program to define detection targets, which will be used against the whole dataset of street images to search for similarity. Finally, a map of similarity will be extracted to demonstrate areas of interest for further investigation. A similar method can be used not only for analysis but also for regeneration of a new image set which is based on selected and detected objects from the city. The project manages to combine the individual and urban scale of materiality through machine learning and data mining.



Professor / 

Baerbel Mueller

Assistants / 

Gregorio Lubroth

Collaboration / 

University of Damascus

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