An introduction to a dynamic plant-wide optimization strategy for an integrated plant. - Thidarat Tosukhowong; Jong Min Lee 002; Jay H. Lee; Joseph Lu (Comput. Chem. Eng., 2004)

A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control. - Jong Min Lee 002 (2004)

Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes. - Jong Min Lee 002; Jay H. Lee (Autom., 2005)

Flux balance analysis in the era of metabolomics. - Jong Min Lee 002; Erwin P. Gianchandani; Jason A. Papin (Briefings Bioinform., 2006)

Approximate dynamic programming based approach to process control and scheduling. - Jay H. Lee; Jong Min Lee 002 (Comput. Chem. Eng., 2006)

Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks. - Jong Min Lee 002; Erwin P. Gianchandani; James A. Eddy; Jason A. Papin (PLoS Comput. Biol., 2008)

Probabilistic modeling and dynamic optimization for performance improvement and risk management of plant-wide operation. - Yu Yang 003; Jong Min Lee 002 (Comput. Chem. Eng., 2010)

A tighter cut generation strategy for acceleration of Benders decomposition. - Yu Yang 003; Jong Min Lee 002 (Comput. Chem. Eng., 2012)

Robust leak detection and its localization using interval estimation for water distribution network. - Yeonsoo Kim; Shin Je Lee; Taekyoon Park; Gibaek Lee; Jung Chul Suh; Jong Min Lee 002 (Comput. Chem. Eng., 2016)

Iterative learning model predictive control for constrained multivariable control of batch processes. - Se-Kyu Oh; Jong Min Lee 002 (Comput. Chem. Eng., 2016)

Point-to-point iterative learning model predictive control. - Se-Kyu Oh; Byung Jun Park; Jong Min Lee 002 (Autom., 2018)

Enhancement of modifier adaptation scheme via feedforward decision maker using historical disturbance data and deep machine learning. - Dong Hwi Jeong; Jong Min Lee 002 (Comput. Chem. Eng., 2018)

A POMDP framework for integrated scheduling of infrastructure maintenance and inspection. - Jong Woo Kim; Go Bong Choi; Jong Min Lee 002 (Comput. Chem. Eng., 2018)

NARX modeling for real-time optimization of air and gas compression systems in chemical processes. - Won Je Lee; Jonggeol Na; Kyeongsu Kim; Chul-Jin Lee; Young-Geun Lee; Jong Min Lee 002 (Comput. Chem. Eng., 2018)

Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics. - Seongeon Park; Jonggeol Na; Minjun Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2018)

Efficient online model-based design of experiments via parameter subset selection for batch dynamical systems. - Jung Hun Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2019)

Hybrid Nonlinear Model Predictive Control of LNT and Urealess SCR Aftertreatment System. - Yeonsoo Kim; Taekyoon Park; Changho Jung; ChangHwan Kim; Yong Wha Kim; Jong Min Lee 002 (IEEE Trans. Control. Syst. Technol., 2019)

Convergence analysis of the deep neural networks based globalized dual heuristic programming. - Jong Woo Kim; Tae Hoon Oh; Sang Hwan Son; Dong Hwi Jeong; Jong Min Lee 002 (Autom., 2020)

Ensemble learning based latent variable model predictive control for batch trajectory tracking under concept drift. - Dong Hwi Jeong; Jong Min Lee 002 (Comput. Chem. Eng., 2020)

Data-driven fault diagnosis for chemical processes using transfer entropy and graphical lasso. - Hodong Lee; Changsoo Kim; Sanha Lim; Jong Min Lee 002 (Comput. Chem. Eng., 2020)

Model-plant mismatch learning offset-free model predictive control. - Sang Hwan Son; Jong Woo Kim; Tae Hoon Oh; Jong Min Lee 002 (CoRR, 2020)

Idle speed control with low-complexity offset-free explicit model predictive control in presence of system delay. - Sang Hwan Son; Se-Kyu Oh; Byung Jun Park; Min Jun Song; Jong Min Lee 002 (CoRR, 2020)

Multirate moving horizon estimation combined with parameter subset selection. - Jaehan Bae; Yeonsoo Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2021)

Model-based reinforcement learning and predictive control for two-stage optimal control of fed-batch bioreactor. - Jong Woo Kim; Byung Jun Park; Tae Hoon Oh; Jong Min Lee 002 (Comput. Chem. Eng., 2021)

Real-time synchronization with expected distribution of synchronized index for on-line monitoring of uneven multiphase batch process. - Hye Ji Lee; Jaehan Bae; Dong Hwi Jeong; Jong Min Lee 002 (Comput. Chem. Eng., 2021)

Design of switching multilinear model predictive control using gap metric. - Byung Jun Park; Yeonsoo Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2021)

Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences. - Sang Hwan Son; Byung Jun Park; Tae Hoon Oh; Jong Woo Kim; Jong Min Lee 002 (Int. J. Control, 2021)

Primal-dual differential dynamic programming: A model-based reinforcement learning for constrained dynamic optimization. - Jong Woo Kim; Tae Hoon Oh; Sang Hwan Son; Jong Min Lee 002 (Comput. Chem. Eng., 2022)

Sparse Bayesian long short-term memory networks for computationally efficient stochastic modeling of plasma etch processes. - Damdae Park; Sangwon Ryu; Gon-Ho Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2022)

Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. - R. Bhushan Gopaluni; Aditya Tulsyan; Benoît Chachuat; Biao Huang 001; Jong Min Lee 002; Faraz Amjad; Seshu Kumar Damarla; Jong Woo Kim; Nathan P. Lawrence (CoRR, 2022)

Techno-economic analysis and process optimization of a PET chemical recycling process based on Bayesian optimization. - Jae Jung Urm; Jae Hwan Choi; Chan Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2023)

Optimization of Fischer-Tropsch microchannel reactor using computational fluid dynamics and enveloped Bayesian optimization. - Kyoungmin Lee; Jong Min Lee 002 (Comput. Chem. Eng., 2024)

Machine learning for industrial sensing and control: A survey and practical perspective. - Nathan P. Lawrence; Seshu Kumar Damarla; Jong Woo Kim; Aditya Tulsyan; Faraz Amjad; Kai Wang 024; Benoît Chachuat; Jong Min Lee 002; Biao Huang 001; R. Bhushan Gopaluni (CoRR, 2024)

Multimodal learning with missing modality for chemical process system. - Suk Hoon Choi; Jong Min Lee 002 (Comput. Chem. Eng., 2025)

Two-stage dynamic real-time optimization framework using parameter-dependent differential dynamic programming. - Hyein Jung; Jong Woo Kim; Jong Min Lee 002 (Comput. Chem. Eng., 2025)

ChemDT: A stochastic decision transformer for chemical process control. - Junseop Shin; Joonsoo Park; Jaehyun Shim; Jong Min Lee 002 (Comput. Chem. Eng., 2025)

A diffusion-attention-based algorithm for optimal spatio-temporal sensor placement in distributed parameter systems. - Yeong Woo Son; Jong Min Lee 002 (Comput. Chem. Eng., 2025)

Decoding industrial-scale battery manufacturing process through integration of causal graphs into explainable artificial intelligence. - Haechang Kim; Ji Young Yun; Eunjoo Jung; Bora Lee; Hyeongseok Kim; Jong Min Lee 002 (Eng. Appl. Artif. Intell., 2025)

Self-Explanatory Fault Diagnosis Framework for Industrial Processes Using Graph Attention. - Chae Sun Kim; Han Bit Kim; Jong Min Lee 002 (IEEE Trans. Ind. Informatics, 2025)