Stone Synergy: AI-Driven Community Housing
The research project proposes an artificial intelligence-driven platform that integrates participatory design, machine learning, and robotic fabrication to address global climate and housing crises. The initiative develops a comprehensive workflow allowing communities to co-design sustainable living environments using an intuitive configurator interface. Machine learning algorithms synthesize community inputs with crowdsourced local material data—including stone, recycled wood, and bamboo—to generate structurally viable and culturally responsive architectural solutions. By employing post-tensioned structural systems, the project enables the utilization of irregular natural materials for modular mass housing, reducing dependency on carbon-intensive industrial supplies and specialized labor. STNE-O establishes new methodologies for community-engaged sustainable design and circular material economies, particularly within vulnerable contexts. Ultimately, the project repositions AI as a facilitator of ecological and social resilience, offering a scalable, replicable paradigm for urban development that prioritizes community well-being and regional material diversity.
The research project proposes an artificial intelligence-driven platform that integrates participatory design, machine learning, and robotic fabrication to address global climate and housing crises. The initiative develops a comprehensive workflow allowing communities to co-design sustainable living environments using an intuitive configurator interface. Machine learning algorithms synthesize community inputs with crowdsourced local material data—including stone, recycled wood, and bamboo—to generate structurally viable and culturally responsive architectural solutions. By employing post-tensioned structural systems, the project enables the utilization of irregular natural materials for modular mass housing, reducing dependency on carbon-intensive industrial supplies and specialized labor. STNE-O establishes new methodologies for community-engaged sustainable design and circular material economies, particularly within vulnerable contexts. Ultimately, the project repositions AI as a facilitator of ecological and social resilience, offering a scalable, replicable paradigm for urban development that prioritizes community well-being and regional material diversity.
- 2025
- Grantee: Olivia Shuning Chen
Olivia Shuning Chen is an architectural designer and researcher. She currently serves as a Guest Speaker and Senior Research Assistant at the University of Hong Kong, while also teaching as a Lecturer in the School of Creative Arts at Hong Kong Baptist University. Her teaching spans design research, environmental architecture, digital methods, and 3D software fundamentals and prototyping. Her expertise lies at the intersection of computational design, digital fabrication, and architectural automation. She is dedicated to examining contemporary architecture and urbanism through these technological lenses, exploring their impact on design development processes and political dimensions. Her work bridges advanced computational research with practical applications in design and making.