Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …

Automated design synthesis has the potential to revolutionize the modern engineering
design process and improve access to highly optimized and customized products across …

Structural topology optimization, which aims to find the optimal physical structure that
maximizes mechanical performance, is vital in engineering design applications in …

Deep generative models such as Variational Autoencoders (VAEs), Generative Adversarial
Networks (GANs), Diffusion Models, and Transformers, have shown great promise in a …

Deep learning is currently being hyped as an almost magical tool for solving all kinds of
difficult problems that computers have not been able to solve in the past. Particularly in the …

Data-driven intelligent computational design (DICD) is a research hotspot that emerged
under fast-develo** artificial intelligence. It emphasizes utilizing deep learning algorithms …

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and
DALL-E, in real-world applications necessitates vast, domain-specific, and publicly …

Abstract Machine learning has recently made significant strides in reducing design cycle
time for complex products. Ship design, which currently involves years-long cycles and small …

In product development, decisions about the appearance of the product are risky and difficult
to make. Engineers and designers are aware that adding new design features or form …

This paper demonstrates how Automated Machine Learning (AutoML) methods can be used
as effective surrogate models in engineering design problems. To do so, we consider the …