Assessment and diagnosis of feedforward/feedback control system. - Junghui Chen; Yuezhi Yea (ACC, 2005)

Intelligent Experimental Design Using an Artificial Neural Network Meta Model and Information Theory. - Shi-Shang Jang; David Shan-Hill Wong; Junghui Chen (Integrated Intelligent Systems for Engineering Design, 2006)

Development of MBPLS Based Control for Serial Operation Processes. - Junghui Chen; Ren-Kai Tsai (CSIE (4), 2009)

Simultaneous data reconciliation and gross error detection for dynamic systems using particle filter and measurement test. - Zhengjiang Zhang; Junghui Chen (Comput. Chem. Eng., 2014)

Correntropy based data reconciliation and gross error detection and identification for nonlinear dynamic processes. - Zhengjiang Zhang; Junghui Chen (Comput. Chem. Eng., 2015)

Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion. - Mifeng Ren; Ting Cheng; Junghui Chen; Xinying Xu; Lan Cheng (Entropy, 2016)

Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework. - Zhiqiang Ge; Junghui Chen (IEEE Trans. Ind. Informatics, 2016)

Soft sensors of nonlinear industrial processes based on self-learning kernel regression model. - Chihang Wei; Junghui Chen; Zhihuan Song; Chun-I Chen (ASCC, 2017)

Probabilistic uncertainty based simultaneous process design and control with iterative expected improvement model. - Lester Lik Teck Chan; Junghui Chen (Comput. Chem. Eng., 2017)

Development of Decay Based PLS Model and Its Economic Run-to-Run Control for Semiconductor Processes. - Pengcheng Lu; Junghui Chen; Lei Xie 007 (ACC, 2018)

Fault diagnosis for processes with feedback control loops by shifted output sampling approach. - Kai Wang 024; Junghui Chen; Zhihuan Song (J. Frankl. Inst., 2018)

A new excitation scheme for closed-loop subspace identification using additional sampling outputs and its extension to instrumental variable method. - Kai Wang 024; Junghui Chen; Zhihuan Song (J. Frankl. Inst., 2018)

Fault Detection Based on Variational Autoencoders for Complex Nonlinear Processes. - Kai Wang 024; Junghui Chen; Zhihuan Song (ASCC, 2019)

Reducing Cost of Process Modeling through Multi-source Data Transfer Learning. - Lester Lik Teck Chan; Junghui Chen (ASCC, 2019)

Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes. - Kai Wang 024; Michael G. Forbes; R. Bhushan Gopaluni; Junghui Chen; Zhihuan Song (IEEE Access, 2019)

Enhancing performance of generalized minimum variance control via dynamic data reconciliation. - Zhengjiang Zhang; Junghui Chen (J. Frankl. Inst., 2019)

Concurrent Fault Detection and Anomaly Location in Closed-Loop Dynamic Systems With Measured Disturbances. - Kai Wang 024; Junghui Chen; Zhihuan Song (IEEE Trans Autom. Sci. Eng., 2019)

Development of Self-Learning Kernel Regression Models for Virtual Sensors on Nonlinear Processes. - Chihang Wei; Junghui Chen; Zhihuan Song; Chun-I Chen (IEEE Trans Autom. Sci. Eng., 2019)

Performance Analysis of Dynamic PCA for Closed-Loop Process Monitoring and Its Improvement by Output Oversampling Scheme. - Kai Wang 024; Junghui Chen; Zhihuan Song (IEEE Trans. Control. Syst. Technol., 2019)

Diagnosis of Nonlinearity-induced Oscillations in Process Control Loops Based on Adaptive Chirp Mode Decomposition. - Qiming Chen; Junghui Chen; Xun Lang; Lei Xie 007; Chenglong Jiang; Hongye Su (ACC, 2020)

Prognostics of tool failing behavior based on autoassociative Gaussian process regression for semiconductor manufacturing. - Li Zhu; Junghui Chen; Chun-I Chen (ICIT, 2020)

Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables. - Jingxiang Liu; Dan Wang 001; Junghui Chen; Jie Hou (IEEE Access, 2020)

Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction. - Kai Wang 024; R. Bhushan Gopaluni; Junghui Chen; Zhihuan Song (IEEE Trans. Ind. Informatics, 2020)

Dual-layer feature extraction based soft sensor methods and applications to industrial polyethylene processes. - Jingxiang Liu; Jie Hou; Junghui Chen (Comput. Chem. Eng., 2021)

Self-tuning variational mode decomposition. - Qiming Chen; Junghui Chen; Xun Lang; Lei Xie 007; Naveed ur Rehman; Hongye Su (J. Frankl. Inst., 2021)

Statistical information based two-layer model predictive control with dynamic economy and control performance for non-Gaussian stochastic process. - Mifeng Ren; Junghui Chen; Peng Shi 001; Gaowei Yan; Lan Cheng (J. Frankl. Inst., 2021)

Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring. - Kai Wang 024; Xiaofeng Yuan; Junghui Chen; Yalin Wang 003 (Neural Networks, 2021)

Semi-Supervised Learning-Based Calibration Model Building of NIR Spectroscopy for In Situ Measurement of Biochemical Processes Under Insufficiently and Inaccurately Labeled Samples. - Guoqing Mu; Tao Liu 002; Chuang Xue; Junghui Chen (IEEE Trans. Instrum. Meas., 2021)

Enhancing Monitoring Performance of Pharmaceutical Processes Using Dual-Attention Latent Dynamic Conditional State-Space Model. - Yi Shan Lee; Junghui Chen (ASCC, 2022)

Performance assessment for non-Gaussian systems by minimum entropy control and dynamic data reconciliation. - Mifeng Ren; Wen Zhang; Junghui Chen; Peng Shi 001; Gaowei Yan (J. Frankl. Inst., 2022)

Using source data to aid and build variational state-space autoencoders with sparse target data for process monitoring. - Yi Shan Lee; Junghui Chen (Neural Networks, 2022)

Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling. - Guoqing Mu; Junghui Chen (IEEE Trans. Instrum. Meas., 2022)

Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy. - Guoqing Mu; Tao Liu 002; Junghui Chen; Chao Shang 002; Chongquan Zhong (IEEE Trans. Instrum. Meas., 2022)

Establishing Convolutional Neural Network Kalman Recurrent Variational Autoencoder Using Infrared Imaging for Process Monitoring: An Application in Spinning Disk Processes. - Yongci Zhang; Yi Shan Lee; Huanting Lin; Junghui Chen (IEEE Trans. Instrum. Meas., 2022)

Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring. - Kai Wang 024; Junghui Chen; Zhihuan Song; Yalin Wang 003; Chunhua Yang 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Tensor slow feature analysis and its applications for batch process monitoring. - Jingxiang Liu; Guoqing Mu; Junghui Chen (Comput. Chem. Eng., 2023)

Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control. - Runze Lin; Yangyang Luo; Xialai Wu; Junghui Chen; Biao Huang 001; Lei Xie 007; Hongye Su (CoRR, 2023)

In Situ Measurement of 2-D Crystal Size Distribution During Cooling Crystallization Process via a Binocular Telecentric Imaging System. - Ji Fan; Tao Liu 002; Yan Huo; Yonghong Tan 001; Junghui Chen (IEEE Trans. Instrum. Meas., 2023)

Deep Learning-Based Binocular Image Analysis for In Situ Measurement of Particle Length Distribution During Crystallization Process. - Ji Fan; Tao Liu 002; Yongcan Shuang; Bo Song; Junghui Chen; Yonghong Tan 001 (IEEE Trans. Instrum. Meas., 2023)

Accelerating reinforcement learning with case-based model-assisted experience augmentation for process control. - Runze Lin; Junghui Chen; Lei Xie 007; Hongye Su (Neural Networks, 2023)

Enhancing Fault Sample Generation Through Physical Knowledge Guidance. - Guoqing Mu; Ching-Lien Liu; Li Zhu; Junghui Chen (ASCC, 2024)

A Fast Predictive Control Method for Vehicle Path Tracking Based on a Recurrent Neural Network. - Xialai Wu; Ling Lin; Junghui Chen; Shuxin Du (IEEE Access, 2024)

A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology. - Wenxue Han; Weiming Shao; Chihang Wei; Wei Song; Can Chen; Junghui Chen (Adv. Eng. Informatics, 2024)

A concise subspace projection based meta-learning method for fast modeling and monitoring in multi-grade semiconductor process. - Jingxiang Liu; Weimin Zhu; Guoqing Mu; Chun-I Chen; Junghui Chen (Comput. Ind. Eng., 2024)

Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives. - Runze Lin; Junghui Chen; Lei Xie 007; Hongye Su; Biao Huang 001 (CoRR, 2024)

A robust semi-supervised learning scheme for development of within-batch quality prediction soft-sensors. - Yi Shan Lee; Junghui Chen (Eng. Appl. Artif. Intell., 2024)

Automatic segmentation of dynamic and static models based on high order slow feature analysis and principal component analysis for multiphase batch monitoring. - Jingxiang Liu; Pin-Hsun Chen; Junghui Chen (Expert Syst. Appl., 2024)

A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks. - Weiming Shao; Xu Li; Yupeng Xing; Junghui Chen (Expert Syst. Appl., 2024)

A Priori Knowledge-Based Dual Hierarchical RNN for Spatial-Temporal Process Modeling: Using a Multitubular Reactor as a Case Study. - Pei Sun; Junghui Chen; Haoyi Que (IEEE Trans. Ind. Informatics, 2024)

Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes. - Li Zhu; Junghui Chen; Chun-I Chen (IEEE Trans. Syst. Man Cybern. Syst., 2024)

A novel reinforced incomplete cyber-physics ensemble with error compensation learning for within-batch quality prediction. - Yi Shan Lee; Junghui Chen (Adv. Eng. Informatics, 2025)

Erratum to "A robust semi-supervised learning scheme for development of within-batch quality prediction soft-sensors"[Eng. Appl. Artif. Intell. 133 (2024) 107920]. - Yi Shan Lee; Junghui Chen (Eng. Appl. Artif. Intell., 2025)

Collaborative twin actors framework using deep deterministic policy gradient for flexible batch processes. - Xindong Wang; Zidong Liu; Junghui Chen (Neural Networks, 2025)

Integrating physical knowledge for generative-based zero-shot learning models in process fault diagnosis. - Guoqing Mu; Ching-Lien Liu; Junghui Chen (Reliab. Eng. Syst. Saf., 2025)

Semi-Supervised Robust Hidden Markov Regression for Large-Scale Time-Series Industrial Data Analytics and its Applications to Soft Sensing. - Weiming Shao; Wenxue Han; Chuanfa Xiao; Lei Chen; Meng-Qin Yu; Junghui Chen (IEEE Trans Autom. Sci. Eng., 2025)

Noninvasive Stereoscopic Backlight Imaging Design for In Situ Measurement of Particle Size Distribution During Continuous Crystallization via COBC. - Ji Fan; Tao Liu 002; Yongcan Shuang; Mingyan Zhao; Haibo Niu; Junghui Chen; Yonghong Tan 001 (IEEE Trans. Instrum. Meas., 2025)

Attention-Driven Supervised Dynamic Latent Variable Models for Monitoring Dynamic Industrial Process. - Jingxiang Liu; Guoqing Mu; Junghui Chen (IEEE Trans. Instrum. Meas., 2025)

Near-Infrared Spectrum Calibration by Deep Dictionary Learning Regression With Data Augmentation for In-Situ Moisture Measurement of Fluidized Bed Drying Process. - Qin Zhang; Tao Liu 002; Junghui Chen; Jingxiang Liu; Qi Zhang; Hongbin Zhang (IEEE Trans. Instrum. Meas., 2025)

Multi-Mode Process Control Using Multi-Task Inverse Reinforcement Learning. - Runze Lin; Junghui Chen; Biao Huang 001; Lei Xie 007; Hongye Su (CoRR, 2025)