Wei Chen

Orcid: 0000-0001-8305-0035

Affiliations:
  • Northwestern University, Department of Mechanical Engineering, Evanston, IL, USA
  • Shanghai Jiao Tong University, China
  • Georgia Institute of Technology, Department of Mechanical Engineering, Atlanta, GA, USA (PhD 1995)


According to our database1, Wei Chen authored at least 49 papers between 2009 and 2025.

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Bibliography

2025
Uncertainty quantification driven machine learning for improving model accuracy in imbalanced regression tasks.
Expert Syst. Appl., 2025

2024
Engineering software 2.0 by interpolating neural networks: unifying training, solving, and calibration.
CoRR, 2024

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning.
CoRR, 2024

2023
Fully Bayesian Inference for Latent Variable Gaussian Process Models.
SIAM/ASA J. Uncertain. Quantification, December, 2023

B-factor prediction in proteins using a sequence-based deep learning model.
Patterns, September, 2023

MolSets: Molecular Graph Deep Sets Learning for Mixture Property Modeling.
CoRR, 2023

Statistical Parameterized Physics-Based Machine Learning Digital Twin Models for Laser Powder Bed Fusion Process.
CoRR, 2023

Mixed-Variable Global Sensitivity Analysis For Knowledge Discovery And Efficient Combinatorial Materials Design.
CoRR, 2023

Physics-aware differentiable design of magnetically actuated kirigami for shape morphing.
CoRR, 2023

Data-Driven Design for Metamaterials and Multiscale Systems: A Review.
CoRR, 2023

Two-scale data-driven design for heat manipulation.
CoRR, 2023

2022
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data.
CoRR, 2022

Uncertainty-aware Mixed-variable Machine Learning for Materials Design.
CoRR, 2022

T-METASET: Task-Aware Generation of Metamaterial Datasets by Diversity-Based Active Learning.
CoRR, 2022

Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty.
CoRR, 2022

A Weighted Statistical Network Modeling Approach to Product Competition Analysis.
Complex., 2022

2021
An Electrochemical Ti3C2Tx Aptasensor for Sensitive and Label-Free Detection of Marine Biological Toxins.
Sensors, 2021

Transfer Learned Designer Polymers For Organic Solar Cells.
J. Chem. Inf. Model., 2021

Towards Improving the Efficiency of Organic Solar Cells by Coarse-Grained Atomistic Modeling of Processing Dependent Morphologies.
Comput. Sci. Eng., 2021

Deep Generative Models for Geometric Design Under Uncertainty.
CoRR, 2021

Enhancing Data-driven Multiscale Topology Optimization with Generalized De-homogenization.
CoRR, 2021

Remixing Functionally Graded Structures: Data-Driven Topology Optimization with Multiclass Shape Blending.
CoRR, 2021

Mechanical Cloak via Data-Driven Aperiodic Metamaterial Design.
CoRR, 2021

Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors.
CoRR, 2021

Data-Driven Multiscale Design of Cellular Composites with Multiclass Microstructures for Natural Frequency Maximization.
CoRR, 2021

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design.
CoRR, 2021

A Graph Neural Network Approach for Product Relationship Prediction.
CoRR, 2021

Range-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis.
CoRR, 2021

Combinatorial semi-bandit in the non-stationary environment.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020
A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors.
Technometrics, 2020

MO-PaDGAN: Reparameterizing Engineering Designs for Augmented Multi-objective Optimization.
CoRR, 2020

MO-PaDGAN: Generating Diverse Designs with Multivariate Performance Enhancement.
CoRR, 2020

Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems.
CoRR, 2020

Data-Driven Topology Optimization with Multiclass Microstructures using Latent Variable Gaussian Process.
CoRR, 2020

METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design.
CoRR, 2020

PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs.
CoRR, 2020

2019
Label-Free Detection of E. coli O157: H7 DNA Using Light-Addressable Potentiometric Sensors with Highly Oriented ZnO Nanorod Arrays.
Sensors, 2019

A Conditional Generative Model for Predicting Material Microstructures from Processing Methods.
CoRR, 2019

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design.
CoRR, 2019

An in-vivo bioelectronic nose using bioengineered olfactory system of rat as sensitive elements towards explosive detection.
Proceedings of the IEEE International Symposium on Olfaction and Electronic Nose, 2019

Formalized Task Characterization for Human-Robot Autonomy Allocation.
Proceedings of the International Conference on Robotics and Automation, 2019

2018
A Network-Based Approach to Modeling and Predicting Product Coconsideration Relations.
Complex., 2018

2017
An Ontology for a Polymer Nanocomposite Community Data Resource.
Proceedings of the 2017 ACM on Web Science Conference, 2017

2016
Time-variant reliability assessment through equivalent stochastic process transformation.
Reliab. Eng. Syst. Saf., 2016

2013
Lightweight design of vehicle parameters under crashworthiness using conservative surrogates.
Comput. Ind., 2013

Computational microstructure characterization and reconstruction for stochastic multiscale material design.
Comput. Aided Des., 2013

2012
Use of support vector regression in structural optimization: Application to vehicle crashworthiness design.
Math. Comput. Simul., 2012

2009
Product Attribute Function Deployment (PAFD) for Decision-Based Conceptual Design.
IEEE Trans. Engineering Management, 2009

Health Management Allocation During Conceptual System Design.
J. Comput. Inf. Sci. Eng., 2009


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