{"id":67959,"date":"2025-07-30T13:02:46","date_gmt":"2025-07-30T17:02:46","guid":{"rendered":"https:\/\/cws.charlotte.edu\/backup-coaa\/?p=67959"},"modified":"2025-07-30T13:04:11","modified_gmt":"2025-07-30T17:04:11","slug":"advancing-the-use-of-generative-ai-in-architectural-research","status":"publish","type":"post","link":"https:\/\/cws.charlotte.edu\/backup-coaa\/2025\/07\/30\/advancing-the-use-of-generative-ai-in-architectural-research\/","title":{"rendered":"Advancing the Use of Generative AI in Architectural Research"},"content":{"rendered":"\n

Interdisciplinary design research was on display July 25 at the Office of Undergraduate Research (OUR) Summer Research Symposium<\/a>, where Assistant Professor of Architecture Sabri G\u00f6kmen<\/a> and his two summer research scholars presented their project, “Prompt-to-Geometry: Exploring Large Language Models for Generative Python Scripting in Architectural Design.”<\/p>\n\n\n\n

Juniors Aidan Oh, a computer science major, and Andrei Vince, a computer engineering major, earned a stipend and insight into the field of architecture working with G\u00f6kmen during their 12-week OUR program.<\/p>\n\n\n\n

Here was their challenge: You\u2019re an architect, and you want to use AI to quickly produce a 3D architectural visualization from a verbal description. How should you describe your building, and how can you make sure the AI will accurately transmit your concepts into an image or model?<\/p>\n\n\n\n

\u201cGenerative tools frequently lack the precision needed for architectural applications,\u201d said Vince in the students\u2019 symposium poster presentation.<\/p>\n\n\n\n

You\u2019re an architect, and you want to use AI to quickly produce a 3D architectural visualization from a verbal description. How should you describe your building, and how can you make sure the AI will accurately transmit your concepts into an image or model?<\/p><\/blockquote><\/figure>\n\n\n\n

In a kind of reverse engineering, working from an image backwards, the students \u201ctaught\u201d generative AI to recognize text prompts to produce photorealistic renderings of geometric structures.<\/p>\n\n\n\n

\n
\"AI-generated<\/figure>\n\n\n\n
\"AI-rendered<\/figure>\n\n\n\n
\"AI-generated<\/figure>\n<\/div>\n\n\n\n

\u201cWe created a Python (programming language) that can understand architectural descriptions in natural language and also automatically produce complex models and detailed images,\u201d Oh said in the presentation.<\/p>\n\n\n\n

Whereas a designer working without AI might take hours to produce a 3D visualization, the automation that the students developed can produce the image in 17 seconds.<\/p>\n\n\n\n

G\u00f6kmen is a computational designer, researcher and educator with over a decade of expertise in parametric modeling, generative art, digital fabrication and software development. He said that this research both explored the capacities of the technology and also how to more precisely use words to generate architectural imagery. It is a skill he will be helping students develop this academic year as the School of Architecture\u2019s second year studio coordinator.<\/p>\n\n\n\n

\u201cAs architects, I don\u2019t think we know how to describe things yet,\u201d he said. \u201cWe\u2019re 3D thinkers.\u201d<\/p>\n\n\n\n

Learn more about their research project here<\/a>.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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