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Drag-guided diffusion models for vehicle image generation
Denoising diffusion models trained at web-scale have revolutionized image generation.
Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings
Generative AI models have made significant progress in automating the creation of 3D shapes, which has the potential to transform car design.
Multi-modal Machine Learning for Vehicle Rating Predictions Using Image, Text, and Parametric Data
Our study underscores the importance of the data-driven multi-modal learning approach for vehicle design, evaluation, and optimization.
ADVISE: AI-accelerated Design of Evidence Synthesis for Global Development
We explore the effectiveness of the human-AI hybrid team in accelerating the evidence synthesis process.
Multi-modal Machine Learning in Engineering Design: A Review and Future Directions
In the rapidly advancing field of multi-modal machine learning (MMML), the convergence of multiple data modalities has the potential to reshape various applications.
Patent Data for Engineering Design: A Critical Review and Future Directions
Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents.
