S. Joe Qin

Orcid: 0000-0001-7631-2535

According to our database1, S. Joe Qin authored at least 101 papers between 1994 and 2024.

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

Awards

IEEE Fellow

IEEE Fellow 2011, "For contributions to model predictive control technology and fault diagnosis in industrial processes".

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Cognitive-Inspired Deep Learning Models for Aspect-Based Sentiment Analysis: A Retrospective Overview and Bibliometric Analysis.
Cogn. Comput., November, 2024

Bidirectional Dynamic Latent Variable Analysis for Closed-Loop Process Monitoring.
IEEE Trans. Ind. Electron., August, 2024

Semi-Supervised Dynamic Latent Variable Regression for Prediction and Quality-Relevant Fault Monitoring.
IEEE Trans. Control. Syst. Technol., July, 2024

Exploring ChatGPT-based Augmentation Strategies for Contrastive Aspect-based Sentiment Analysis.
CoRR, 2024

Probabilistic Reduced-Dimensional Vector Autoregressive Modeling with Oblique Projections.
CoRR, 2024

A PLS-Integrated Lasso Method With Application in Index Tracking.
Proceedings of the IEEE International Conference on Acoustics, 2024

Data-driven approaches for satellite SADA system health monitoring with limited data.
Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

2023
Knowledge-Informed Sparse Learning for Relevant Feature Selection and Optimal Quality Prediction.
IEEE Trans. Ind. Informatics, December, 2023

Attention-mechanism based DiPLS-LSTM and its application in industrial process time series big data prediction.
Comput. Chem. Eng., August, 2023

Applying and dissecting LSTM neural networks and regularized learning for dynamic inferential modeling.
Comput. Chem. Eng., July, 2023

Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.
CoRR, 2023

MLPST: MLP is All You Need for Spatio-Temporal Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Latent Dynamic Networked System Identification with High-Dimensional Networked Data.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Probabilistic Reduced-Dimensional Vector Autoregressive Modeling for Dynamics Prediction and Reconstruction with Oblique Projections.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Low-Dimensional Latent State Space Identification with Application to the Shell Control Process.
Proceedings of the IEEE Conference on Control Technology and Applications, 2023

2022
Kernel-Based Statistical Process Monitoring and Fault Detection in the Presence of Missing Data.
IEEE Trans. Ind. Informatics, 2022

Latent State Space Modeling of High-Dimensional Time Series With a Canonical Correlation Objective.
IEEE Control. Syst. Lett., 2022

2021
Guest Editorial Special Issue on Deep Integration of Artificial Intelligence and Data Science for Process Manufacturing.
IEEE Trans. Neural Networks Learn. Syst., 2021

Guest Editorial: Industrial Artificial Intelligence for Smart Manufacturing.
IEEE Trans. Ind. Informatics, 2021

Online Peak-Demand Minimization Using Energy Storage.
CoRR, 2021

Plant-wide troubleshooting and diagnosis using dynamic embedded latent feature analysis.
Comput. Chem. Eng., 2021

Integration of process knowledge and statistical learning for the Dow data challenge problem.
Comput. Chem. Eng., 2021

Optimal Peak-Minimizing Online Algorithms for Large-Load Users with Energy Storage.
Proceedings of the 2021 IEEE Conference on Computer Communications Workshops, 2021

Optimal Online Algorithms for Peak-Demand Reduction Maximization with Energy Storage.
Proceedings of the e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems, Virtual Event, Torino, Italy, 28 June, 2021

Latent Vector Autoregressive Modeling for Reduced Dimensional Dynamic Feature Extraction and Prediction.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

A Non-iterative Partial Least Squares Algorithm for Supervised Learning with Collinear Data.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
Multiscale Kernel Based Residual Convolutional Neural Network for Motor Fault Diagnosis Under Nonstationary Conditions.
IEEE Trans. Ind. Informatics, 2020

Efficient Dynamic Latent Variable Analysis for High-Dimensional Time Series Data.
IEEE Trans. Ind. Informatics, 2020

Modeling inter-layer interactions for out-of-plane shape deviation reduction in additive manufacturing.
IISE Trans., 2020

On the Convergence of the Dynamic Inner PCA Algorithm.
CoRR, 2020

Dynamic latent variable regression for inferential sensor modeling and monitoring.
Comput. Chem. Eng., 2020

Editorial for Tom Edgar special issue in Computers & Chemical Engineering.
Comput. Chem. Eng., 2020

Bridging systems theory and data science: A unifying review of dynamic latent variable analytics and process monitoring.
Annu. Rev. Control., 2020

Dynamic-Inner Canonical Correlation Analysis based Process Monitoring.
Proceedings of the 2020 American Control Conference, 2020

2019
Distributed Approach for Temporal-Spatial Charging Coordination of Plug-in Electric Taxi Fleet.
IEEE Trans. Ind. Informatics, 2019

Advances and opportunities in machine learning for process data analytics.
Comput. Chem. Eng., 2019

Dynamic Processes Modeling and Monitoring based on a Novel Dynamic Latent Variable Model.
Proceedings of the CAA Symposium on Fault Detection, 2019

2018
Dynamic latent variable analytics for process operations and control.
Comput. Chem. Eng., 2018

2017
Unevenly Sampled Dynamic Data Modeling and Monitoring With an Industrial Application.
IEEE Trans. Ind. Informatics, 2017

Autoregressive Dynamic Latent Variable Models for Process Monitoring.
IEEE Trans. Control. Syst. Technol., 2017

Quality-relevant fault detection of nonlinear processes based on kernel concurrent canonical correlation analysis.
Proceedings of the 2017 American Control Conference, 2017

Distributed optimization of multi-building energy systems with spatially and temporally coupled constraints.
Proceedings of the 2017 American Control Conference, 2017

2016
Comprehensive Monitoring of Nonlinear Processes Based on Concurrent Kernel Projection to Latent Structures.
IEEE Trans Autom. Sci. Eng., 2016

Feature selection based on concurrent projection to latent structures for high dimensional spectra data.
Proceedings of the IEEE International Conference on Information and Automation, 2016

Prescriptive analytics for understanding of out-of-plane deformation in additive manufacturing.
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016

Deep causal mining for plant-wide oscillations with multilevel Granger causality analysis.
Proceedings of the 2016 American Control Conference, 2016

2015
Model-Predictive Control in Practice.
Proceedings of the Encyclopedia of Systems and Control, 2015

Out-of-plane geometric error prediction for additive manufacturing.
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2015

2014
Multiblock Concurrent PLS for Decentralized Monitoring of Continuous Annealing Processes.
IEEE Trans. Ind. Electron., 2014

A New Method of Dynamic Latent-Variable Modeling for Process Monitoring.
IEEE Trans. Ind. Electron., 2014

Guest Editorial Integrated Optimization of Industrial Automation.
IEEE Trans Autom. Sci. Eng., 2014

Optimal operational control for complex industrial processes.
Annu. Rev. Control., 2014

Multi-directional reconstruction based contributions for root-cause diagnosis of dynamic processes.
Proceedings of the American Control Conference, 2014

2013
Decentralized Fault Diagnosis of Continuous Annealing Processes Based on Multilevel PCA.
IEEE Trans Autom. Sci. Eng., 2013

Predictive control methods to improve energy efficiency and reduce demand in buildings.
Comput. Chem. Eng., 2013

Experimental study of economic model predictive control in building energy systems.
Proceedings of the American Control Conference, 2013

2012
Single-machine scheduling with advanced process control constraints.
J. Sched., 2012

Discussion on: "Post-Optimality Approach to Prevent Cycling in Linear MPC Target Calculation".
Eur. J. Control, 2012

Survey on data-driven industrial process monitoring and diagnosis.
Annu. Rev. Control., 2012

Feature Selection of Frequency Spectrum for Modeling Difficulty to Measure Process Parameters.
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012

Concurrent projection to latent structures for output-relevant and input-relevant fault monitoring.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Improved genetic algorithm for magnetic material two-stage multi-product production scheduling: A case study.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Non-stationary Kalman filter parametrization of subspace models with applications to MPC.
Proceedings of the American Control Conference, 2012

Control performance monitoring via model residual assessment.
Proceedings of the American Control Conference, 2012

Model predictive control of building energy systems with balanced model reduction.
Proceedings of the American Control Conference, 2012

2011
Data-Based Hybrid Tension Estimation and Fault Diagnosis of Cold Rolling Continuous Annealing Processes.
IEEE Trans. Neural Networks, 2011

Quality Relevant Data-Driven Modeling and Monitoring of Multivariate Dynamic Processes: The Dynamic T-PLS Approach.
IEEE Trans. Neural Networks, 2011

Generalized Reconstruction-Based Contributions for Output-Relevant Fault Diagnosis With Application to the Tennessee Eastman Process.
IEEE Trans. Control. Syst. Technol., 2011

KPCA based multi-spectral segments feature extraction and GA based Combinatorial optimization for frequency spectrum data modeling.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Improving industrial mpc performance with data-driven disturbance modeling.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Modeling CO2 recovery for optimal dynamic operations.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Subspace system identification for CO2 recovery processes.
Proceedings of the 2011 IEEE International Symposium on Computer-Aided Control System Design, 2011

Soft sensing of sodium aluminate solution component concentrations via on-line clustering and fuzzy modeling.
Proceedings of the American Control Conference, 2011

Control performance monitoring of LP-MPC cascade systems.
Proceedings of the American Control Conference, 2011

An adaptive chaotic PSO for parameter optimization and feature extraction of LS-SVM based modelling.
Proceedings of the American Control Conference, 2011

2010
Decentralized Fault Diagnosis of Large-Scale Processes Using Multiblock Kernel Partial Least Squares.
IEEE Trans. Ind. Informatics, 2010

Geometric properties of partial least squares for process monitoring.
Autom., 2010

Progressive Parametrization in Subspace Identification Models with finite horizons.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Tension soft sensor of continuous annealing lines using cascade frequency domain observer with combined PCA and neural networks error compensation.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Online dropout detection in subcutaneously implanted continuous glucose monitoring.
Proceedings of the American Control Conference, 2010

Reconstruction-based contribution for process monitoring with kernel principal component analysis.
Proceedings of the American Control Conference, 2010

2009
Reconstruction-based contribution for process monitoring.
Autom., 2009

2007
Subspace methods for system identification: Tohru Katayama; Springer-Verlag, ISBN: 1-85233-981-0.
Autom., 2007

Monitoring Non-normal Data with Principal Component Analysis and Adaptive Density Estimation.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007

2006
An overview of subspace identification.
Comput. Chem. Eng., 2006

Closed-loop subspace identification using the parity space.
Autom., 2006

2005
A novel subspace identification approach with enforced causal models.
Autom., 2005

2004
A strong tracking predictor for nonlinear processes with input time delay.
Comput. Chem. Eng., 2004

A two-stage iterative learning control technique combined with real-time feedback for independent disturbance rejection.
Autom., 2004

On consistency of closed-loop subspace identification with innovation estimation.
Proceedings of the 43rd IEEE Conference on Decision and Control, 2004

A multi-step supervisory control strategy for semiconductor device manufacturing.
Proceedings of the 43rd IEEE Conference on Decision and Control, 2004

2003
The Character of an Idempotent-analytic Nonlinear Small Gain Theorem.
Proceedings of the Positive Systems, 2003

2002
On the selection of variables for qualitative modelling of dynamical systems.
Int. J. Gen. Syst., 2002

Adaptive run to run control for intermittent batch operations.
Proceedings of the American Control Conference, 2002

Subspace model predictive control and a case study.
Proceedings of the American Control Conference, 2002

Stability analysis of double EWMA run-to-run control with metrology delay.
Proceedings of the American Control Conference, 2002

Drug dosage adjustment via run-to-run control.
Proceedings of the American Control Conference, 2002

2001
Principal component analysis for errors-in-variables subspace identification.
Proceedings of the 40th IEEE Conference on Decision and Control, 2001

Extracting fault subspaces for fault identification of a polyester film process.
Proceedings of the American Control Conference, 2001

An alternative PLS algorithm for the monitoring of industrial process.
Proceedings of the American Control Conference, 2001

1994
A multiregion fuzzy logic controller for nonlinear process control.
IEEE Trans. Fuzzy Syst., 1994


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