Interpretations and Generation through Data
In an increasingly digitised world, the integration of parametric and data-driven design at various scales within the built environment is no longer optional but essential. This thesis cluster brings together research themes that explore the transformative role of computational design and data-informed methodologies in shaping the AEC industry.
While digital tools and processes are advancing rapidly, it is vital to examine their frameworks, workflows, and implications in architecture—the design and materialisation of human-made spaces. Students will propose and investigate how parametric and data-driven approaches can offer innovative solutions to contemporary challenges in the built environment.
Research may involve collecting, analysing, or generating extensive datasets to inform predictive models and optimise design outcomes. By leveraging parametric design and computational techniques, students can explore new ways to enhance architectural creativity, improve spatial performance, and address complex design requirements.
The thesis projects in this cluster aim to develop cutting-edge parametric processes and data-driven strategies for design exploration and optimization, leading to greater efficiency, adaptability, and responsiveness in the built environment.
A Methodological Approach to Urban Growth and Hybrid Energy Systems in the Global South Why Global South ? Urbanization in the Global South is a defining trend of the 21st century, with over 90% of urban growth expected to occur in low- and middle-income countries by 2050. This rapid expansion has led to a surge … Read more
This research explores the optimization of glulam in architectural design by aligning material grading and grain orientation with force trajectories. Combining glulam offcuts and higher-grade timber, the study minimizes waste while maximizing structural efficiency. Computational workflows and generative algorithms are used to design force-aligned components for scalable applications. Prototypes demonstrate enhanced performance and sustainability, offering … Read more
This proposal addresses the challenges of real estate valuation and optimization for retail properties by leveraging advanced technological tools and tailored datasets. The project introduces a platform that integrates environmental, market, and demographic data to provide dynamic and data-driven insights for valuation and optimal property usage. The methodology incorporates machine learning, mapping, and regression analysis … Read more
An Automated Design Solution for Earthquake-Prone Regions How can an machine learning-enhanced parametric design tool develop localized, seismic-resilient low-cost, low-rise modular housing by intelligently integrating material constraints, structural performance, and architectural aesthetics?
