741 citations · 769 across the 7 of their papers we have counts for
15 papers
2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing
Jay Lee, Hanqi Su, Marco Macchi +50
The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency, adaptability, and autonomy ac…
GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects
Nathan Hoffman, Cashen Diniz, Dehao Liu +3
Simulation-based approaches to microstructure generation can suffer from a variety of limitations, such as high memory usage, long computational times, and difficulties in generati…
Inverse design with conditional cascaded diffusion models
Milad Habibi, Mark Fuge
Adjoint-based design optimizations are usually computationally expensive and those costs scale with resolution. To address this, researchers have proposed machine learning approach…
Airfoil Design Parameterization and Optimization using Bézier Generative Adversarial Networks
Wei Chen, Kevin Chiu, Mark Fuge
Global optimization of aerodynamic shapes usually requires a large number of expensive computational fluid dynamics simulations because of the high dimensionality of the design spa…
Forming Diverse Teams from Sequentially Arriving People
Faez Ahmed, John Dickerson, Mark Fuge
Collaborative work often benefits from having teams or organizations with heterogeneous members. In this paper, we present a method to form such diverse teams from people arriving…
Adaptive Expansion Bayesian Optimization for Unbounded Global Optimization
Wei Chen, Mark Fuge
Bayesian optimization is normally performed within fixed variable bounds. In cases like hyperparameter tuning for machine learning algorithms, setting the variable bounds is not tr…