# Designing with Simulations: A New Era for Architecture

Page: https://stenobird.com/podcast/innovation-by-design-7808140/designing-with-simulations-a-new-era-for-architecture
Text version: https://stenobird.com/podcast/innovation-by-design-7808140/designing-with-simulations-a-new-era-for-architecture.md
Podcast: [Innovation by Design](https://stenobird.com/podcast/innovation-by-design-7808140)
Published: 2026-05-11T07:00:00+00:00
Episode link: https://innovationbydesign.captivate.fm
Audio file: https://episodes.captivate.fm/episode/b4a97e4e-2e61-4c28-b539-d8f71774ebb2.mp3
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JSON: https://stenobird.com/v1/public/podcasts/innovation-by-design-7808140/episodes/designing-with-simulations-a-new-era-for-architecture
Duration seconds: 2990

## Resource

In this episode of Innovation By Design , Angelos Chronis explores the growing role of AI in architecture and urban design. We talk about how neural networks and machine learning can accelerate simulations and expand what is practical to test during design, including daylighting and solar exposure studies. We also dig into generative components and optimization workflows in tools like Grasshopper, including the use of genetic algorithms to search design options. Finally, we touch on how creative AI tools such as Midjourney, along with new text and diagram workflows, are changing how designers ideate and communicate. About the guest Angelos Chronis is an architect and researcher working at the intersection of computation, machine learning, and design, with a focus on using AI-enabled workflows to improve analysis, iteration speed, and environmental performance in architecture and urbanism. Links infrared.city website infrared.city team page Angelos Chronis on LinkedIn Angelos on Instagram Angelos on Google Scholar Wikipedia: Machine learning Wikipedia: Artificial intelligence Wikipedia: Artificial neural network Wikipedia: Generative design Scholarpedia: Genetic algorithm Wikipedia: Computational Fluid Dynamics (CFD) NASA CFD intro Wikipedia: Daylighting analysis Midjourney Wikipedia: Generative adversarial network

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## Transcript

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