229 citations · 590 across the 13 of their papers we have counts for
12 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…
Adaptive Digital Twin of Sheet Metal Forming via Proper Orthogonal Decomposition-Based Koopman Operator with Model Predictive Control
Yi-Ping Chen, Derick Suarez, Ying-Kuan Tsai +6
Digital Twin (DT) technologies are transforming manufacturing by enabling real-time prediction, monitoring, and control of complex processes. Yet, applying DT to deformation-based…
MolSets: Molecular Graph Deep Sets Learning for Mixture Property Modeling
Hengrui Zhang, Jie Chen, James M. Rondinelli +1
Recent advances in machine learning (ML) have expedited materials discovery and design. One significant challenge faced in ML for materials is the expansive combinatorial space of…
A Latent Variable Approach for Non-Hierarchical Multi-Fidelity Adaptive Sampling
Yi-Ping Chen, Liwei Wang, Yigitcan Comlek +1
Multi-fidelity (MF) methods are gaining popularity for enhancing surrogate modeling and design optimization by incorporating data from various low-fidelity (LF) models. While most…
Data-Driven Design for Metamaterials and Multiscale Systems: A Review
Doksoo Lee, Wei Wayne Chen, Liwei Wang +2
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 a…
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants
Ruichu Cai, Zhiyi Huang, Wei Chen +2
Causal discovery with latent confounders is an important but challenging task in many scientific areas. Despite the success of some overcomplete independent component analysis (OIC…