Yuwei Mao

Northwestern University — United States

Materials Science · Physical Sciences

8h-index159citations21works4.22yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Learning in Materials Science(10), Metallurgy and Material Forming(3), X-ray Diffraction in Crystallography(3), Microstructure and mechanical properties(2), Respiratory Support and Mechanisms(2)

Publications21 total

Developing and validating machine learning models to predict next-day extubation
Scientific Reports·2025· 2 citedOpen Access
An AI framework for time series microstructure prediction from processing parameters
Scientific Reports·2025· 1 citedOpen Access
MicroProcSim: A Software for Simulation of Microstructure Evolution
Integrating materials and manufacturing innovation·2025· 2 citedOpen Access
Advancing material simulations: Physics-Informed Neural Networks and Object-Oriented Crystal Plasticity Finite Element Methods
International Journal of Plasticity·2024· 13 cited
Deep Learning Based Inverse Modeling for Materials Design: From Microstructure and Property to Processing
2024· 1 cited
Tackling the Nonlinearity Problem in Inverse Modeling: Mixture Density Network-Backed Quantized AutoEncoder
2024
Enhancing Deep Neural Network Classification Performance Through Novel Weight Initialization: t-SNE Supported Walsh Matrix Approach
2024
XElemNet: towards explainable AI for deep neural networks in materials science
Scientific Reports·2024· 12 citedOpen Access
A deep learning-based crystal plasticity finite element model
Scripta Materialia·2024· 13 cited
Developing and validating a machine learning model to predict successful next-day extubation in the ICU
2024· 2 citedOpen Access
Advancing Material Simulations: Physics-Informed Neural Networks and Object-Oriented Crystal Plasticity Finite Element Methods
SSRN Electronic Journal·2024Open Access
A Deep Learning Framework for Time-Series Processing-Microstructure-Property Prediction
2023· 3 cited
Physics-based Data-Augmented Deep Learning for Enhanced Autogenous Shrinkage Prediction on Experimental Dataset
2023· 4 cited
An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems
npj Computational Materials·2023· 15 citedOpen Access
AI for Learning Deformation Behavior of a Material: Predicting Stress-Strain Curves 4000x Faster Than Simulations
2023· 3 cited
MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction
Journal of Chemical Information and Modeling·2023· 23 citedOpen Access
A generative adversarial networks and mixture density networks based inverse modeling for microstructural materials design
Faculty of 1000 Research Ltd·2023Open Access
To Shuffle or Not To Shuffle: Mini-Batch Shuffling Strategies for Multi-class Imbalanced Classification
2022· 3 cited
Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design
Integrating materials and manufacturing innovation·2022· 17 citedOpen Access
A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures
Journal of Intelligent Manufacturing·2022· 36 citedOpen Access
page 1 of 2Next →

Frequent Co-authors

Ankit Agrawal(20), Alok Choudhary(18), Wei‐keng Liao(15), Vishu Gupta(13), Muhammed Nur Talha Kilic(8), Pınar Acar(6), Kewei Wang(5), Mahmudul Hasan(5), Shahriyar Keshavarz(4), Andrew Reid(4), Kamal Choudhary(3), Francesca Tavazza(3), Arindam Paul(3), Youjia Li(3), Alec Peltekian(3), Md. Maruf Billah(3), Zijiang Yang(2), Dipendra Jha(2), C. S. George Lee(2), Kewei Wang(2)