Design Exploration

Design exploration research focuses on developing efficient methods for navigating complex design spaces to find optimal solutions, encompassing diverse fields like 3D graphics, multimodal applications, and urban AI systems. Current approaches leverage AI foundation models, including vision-language models and deep learning, to generate and evaluate design options, often employing novel algorithms like quality-diversity methods and quadratic neural networks for enhanced performance and exploration of feature spaces beyond traditional parametric approaches. This research significantly impacts various domains by automating tedious design tasks, improving the accessibility of design tools for non-experts, and enabling more informed decision-making in complex systems.