Bicycle Design

Bicycle design research is increasingly leveraging AI and machine learning to optimize both the aesthetic and functional aspects of bicycle frames. Current efforts focus on generative models, including diffusion models and graph neural networks, to create novel designs, complete incomplete designs, and predict structural performance from parametric data or images. Large multimodal datasets, pairing CAD models with images and performance metrics, are crucial for training these models and enabling cross-modal predictions. This research improves design efficiency and exploration, offering valuable tools for engineers and designers to create lighter, stronger, and more customized bicycles.