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Deepscope

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Ariel Noyman

by Sarah Beckmann

July 24, 2026

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DeepScope is a novel platform for interactive, real-time, and setup-less urban design visualization. It attempts to substitute common practices of urban design with a machine-learnt, generative visualization approach. By implementing a deep convolutional generative adversarial network (DCGAN) and CityScope, a tangible user interface, this project allows for real-time prototyping and visualizations of urban design processes.

Project Research

The Deep Image of the City

How do you image a city that doesn't exist? DeepScope is a novel platform for interactive, real-time, and setup-less urban design visu…

Deep Image of the City: A generative approach to urban-design visualization

Noyman, Ariel, and Kent Larson. "A deep image of the city: Generative urban-design visualization." Proceedings of the 11th annual symposium on simulation for architecture and urban design. 2020.

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Post Research

Ariel Noyman's work on CityScope selected for the Young Talent exhibition at Hebei International Industrial Design Week (HIDW)

The “HIDW Young Talent” exhibition addressed three topics: Manufacturing of Tomorrow, Future Craft, and City Catalyst.

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Ariel Noyman Dissertation Defense

CityScope: An Urban modeling and Simulation Platform