Zhenyu James Kong

Orcid: 0000-0002-8827-502X

Affiliations:
  • Virginia Tech, Blacksburg, VA, USA


According to our database1, Zhenyu James Kong authored at least 39 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Anomaly detection in additive manufacturing processes using supervised classification with imbalanced sensor data based on generative adversarial network.
J. Intell. Manuf., June, 2024

Process parameter optimization for reproducible fabrication of layer porosity quality of 3D-printed tissue scaffold.
J. Intell. Manuf., April, 2024

WOOD: Wasserstein-Based Out-of-Distribution Detection.
IEEE Trans. Pattern Anal. Mach. Intell., February, 2024

Advancing Additive Manufacturing through Deep Learning: A Comprehensive Review of Current Progress and Future Challenges.
CoRR, 2024

2023
Self-Scalable Tanh (Stan): Multi-Scale Solutions for Physics-Informed Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Correction to: Toward online layer-wise surface morphology measurement in additive manufacturing using a deep learning-based approach.
J. Intell. Manuf., August, 2023

Toward online layer-wise surface morphology measurement in additive manufacturing using a deep learning-based approach.
J. Intell. Manuf., August, 2023

A novel disassembly process of end-of-life lithium-ion batteries enhanced by online sensing and machine learning techniques.
J. Intell. Manuf., June, 2023

Robust Tensor Decomposition Based Background/Foreground Separation in Noisy Videos and Its Applications in Additive Manufacturing.
IEEE Trans Autom. Sci. Eng., 2023

A Sparse Bayesian Learning for Diagnosis of Nonstationary and Spatially Correlated Faults with Application to Multistation Assembly Systems.
CoRR, 2023

2022
Super Resolution for Multi-Sources Image Stream Data Using Smooth and Sparse Tensor Completion and Its Applications in Data Acquisition of Additive Manufacturing.
Technometrics, 2022

Augmented Time Regularized Generative Adversarial Network (ATR-GAN) for Data Augmentation in Online Process Anomaly Detection.
IEEE Trans Autom. Sci. Eng., 2022

Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee.
J. Mach. Learn. Res., 2022

Identifying the Early Signs of Preterm Birth from U.S. Birth Records Using Machine Learning Techniques.
Inf., 2022

Imbalanced Data Classification via Generative Adversarial Network with Application to Anomaly Detection in Additive Manufacturing Process.
CoRR, 2022

Reinforcement Learning-based Defect Mitigation for Quality Assurance of Additive Manufacturing.
CoRR, 2022

A Novel Sparse Bayesian Learning and Its Application to Fault Diagnosis for Multistation Assembly Systems.
CoRR, 2022

Self-scalable Tanh (Stan): Faster Convergence and Better Generalization in Physics-informed Neural Networks.
CoRR, 2022

High-Resolution Shape Deformation Prediction in Additive Manufacturing Using 3D CNN.
Proceedings of the Winter Simulation Conference, 2022

2021
Clustered Discriminant Regression for High-Dimensional Data Feature Extraction and Its Applications in Healthcare and Additive Manufacturing.
IEEE Trans Autom. Sci. Eng., 2021

An integrated manifold learning approach for high-dimensional data feature extractions and its applications to online process monitoring of additive manufacturing.
IISE Trans., 2021

2020
Robust Tensor Principal Component Analysis: Exact Recovery via Deterministic Model.
CoRR, 2020

2019
Layer-wise spatial modeling of porosity in additive manufacturing.
IISE Trans., 2019

2018
A Spectral Graph Theoretic Approach for Monitoring Multivariate Time Series Data From Complex Dynamical Processes.
IEEE Trans Autom. Sci. Eng., 2018

Functional Quantitative and Qualitative Models for Quality Modeling in a Fused Deposition Modeling Process.
IEEE Trans Autom. Sci. Eng., 2018

Robust Sparse Representation-Based Classification Using Online Sensor Data for Monitoring Manual Material Handling Tasks.
IEEE Trans Autom. Sci. Eng., 2018

A Method for Robust Online Classification using Dictionary Learning: Development and Assessment for Monitoring Manual Material Handling Activities Using Wearable Sensors.
CoRR, 2018

2017
Dirichlet Process Gaussian Mixture Models for Real-Time Monitoring and Their Application to Chemical Mechanical Planarization.
IEEE Trans Autom. Sci. Eng., 2017

2016
Online Classification and Sensor Selection Optimization With Applications to Human Material Handling Tasks Using Wearable Sensing Technologies.
IEEE Trans. Hum. Mach. Syst., 2016

Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory.
IEEE Trans Autom. Sci. Eng., 2016

2015
A Generalized Procedure for Monitoring Right-censored Failure Time Data.
Qual. Reliab. Eng. Int., 2015

2013
Fault Diagnosis Using an Enhanced Relevance Vector Machine (RVM) for Partially Diagnosable Multistation Assembly Processes.
IEEE Trans Autom. Sci. Eng., 2013

2011
Development of a structural equation modeling-based decision tree methodology for the analysis of lung transplantations.
Decis. Support Syst., 2011

2010
Process Capability Sensitivity Analysis for Design Evaluation of Multistage Assembly Processes.
IEEE Trans Autom. Sci. Eng., 2010

Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods.
J. Comput. Inf. Sci. Eng., 2010

A machine learning-based approach to prognostic analysis of thoracic transplantations.
Artif. Intell. Medicine, 2010

2009
Predicting the graft survival for heart-lung transplantation patients: An integrated data mining methodology.
Int. J. Medical Informatics, 2009

2008
Supply chain performance with various price-dependent demand functions and component commonality in one product family.
Proceedings of the 2008 IEEE International Conference on Automation Science and Engineering, 2008

Process capability sensitivity analysis for design evaluation of multi station assembly systems.
Proceedings of the 2008 IEEE International Conference on Automation Science and Engineering, 2008


  Loading...