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ORCIDJong Min Lee 0002
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation: Seoul National University, South Korea
Other persons with the same name
- Jongmin Lee (aka: JongMin Lee, Jong-Min Lee, Jong Min Lee) — disambiguation page
- Jong Min Lee 0001 — SK Telecom, Seoul, South Korea (and 2 more)
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Books and Theses
- 2004
[b1]Jong Min Lee:
A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control. Georgia Institute of Technology, Atlanta, GA, USA, 2004
Journal Articles
- 2025
- [j34]Hyein Jung, Jong Woo Kim, Jong Min Lee
:
Two-stage dynamic real-time optimization framework using parameter-dependent differential dynamic programming. Comput. Chem. Eng. 192: 108896 (2025) - [j33]Junseop Shin, Joonsoo Park, Jaehyun Shim, Jong Min Lee:
ChemDT: A stochastic decision transformer for chemical process control. Comput. Chem. Eng. 199: 109155 (2025) - [j32]Yeong Woo Son, Jong Min Lee:
A diffusion-attention-based algorithm for optimal spatio-temporal sensor placement in distributed parameter systems. Comput. Chem. Eng. 200: 109163 (2025) - [j31]Suk Hoon Choi, Jong Min Lee:
Multimodal learning with missing modality for chemical process system. Comput. Chem. Eng. 201: 109196 (2025) - [j30]Haechang Kim, Ji Young Yun, Eunjoo Jung, Bora Lee, Hyeongseok Kim, Jong Min Lee:
Decoding industrial-scale battery manufacturing process through integration of causal graphs into explainable artificial intelligence. Eng. Appl. Artif. Intell. 159: 111657 (2025) - [j29]Chae Sun Kim, Han Bit Kim, Jong Min Lee:
Self-Explanatory Fault Diagnosis Framework for Industrial Processes Using Graph Attention. IEEE Trans. Ind. Informatics 21(4): 3396-3405 (2025) - 2024
- [j28]Kyoungmin Lee, Jong Min Lee:
Optimization of Fischer-Tropsch microchannel reactor using computational fluid dynamics and enveloped Bayesian optimization. Comput. Chem. Eng. 185: 108658 (2024) - 2023
- [j27]Jae Jung Urm, Jae Hwan Choi, Chan Kim, Jong Min Lee:
Techno-economic analysis and process optimization of a PET chemical recycling process based on Bayesian optimization. Comput. Chem. Eng. 179: 108451 (2023) - 2022
- [j26]Damdae Park, Sangwon Ryu, Gon-Ho Kim, Jong Min Lee:
Sparse Bayesian long short-term memory networks for computationally efficient stochastic modeling of plasma etch processes. Comput. Chem. Eng. 159: 107696 (2022) - [j25]Jong Woo Kim, Tae Hoon Oh, Sang Hwan Son, Jong Min Lee:
Primal-dual differential dynamic programming: A model-based reinforcement learning for constrained dynamic optimization. Comput. Chem. Eng. 167: 108004 (2022) - 2021
- [j24]Jaehan Bae, Yeonsoo Kim, Jong Min Lee:
Multirate moving horizon estimation combined with parameter subset selection. Comput. Chem. Eng. 147: 107253 (2021) - [j23]Byung Jun Park, Yeonsoo Kim, Jong Min Lee:
Design of switching multilinear model predictive control using gap metric. Comput. Chem. Eng. 150: 107317 (2021) - [j22]Jong Woo Kim, Byung Jun Park, Tae Hoon Oh, Jong Min Lee:
Model-based reinforcement learning and predictive control for two-stage optimal control of fed-batch bioreactor. Comput. Chem. Eng. 154: 107465 (2021) - [j21]Hye Ji Lee, Jaehan Bae, Dong Hwi Jeong, Jong Min Lee:
Real-time synchronization with expected distribution of synchronized index for on-line monitoring of uneven multiphase batch process. Comput. Chem. Eng. 154: 107490 (2021) - [j20]Sang Hwan Son, Byung Jun Park, Tae Hoon Oh, Jong Woo Kim, Jong Min Lee:
Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences. Int. J. Control 94(11): 3213-3225 (2021) - 2020
- [j19]Jong Woo Kim, Tae Hoon Oh, Sang Hwan Son, Dong Hwi Jeong, Jong Min Lee:
Convergence analysis of the deep neural networks based globalized dual heuristic programming. Autom. 122: 109222 (2020) - [j18]Dong Hwi Jeong, Jong Min Lee:
Ensemble learning based latent variable model predictive control for batch trajectory tracking under concept drift. Comput. Chem. Eng. 139: 106875 (2020) - [j17]Hodong Lee, Changsoo Kim, Sanha Lim, Jong Min Lee:
Data-driven fault diagnosis for chemical processes using transfer entropy and graphical lasso. Comput. Chem. Eng. 142: 107064 (2020) - 2019
- [j16]Jung Hun Kim, Jong Min Lee:
Efficient online model-based design of experiments via parameter subset selection for batch dynamical systems. Comput. Chem. Eng. 121: 646-653 (2019) - [j15]Yeonsoo Kim, Taekyoon Park, Changho Jung, ChangHwan Kim, Yong Wha Kim, Jong Min Lee:
Hybrid Nonlinear Model Predictive Control of LNT and Urealess SCR Aftertreatment System. IEEE Trans. Control. Syst. Technol. 27(5): 2305-2313 (2019) - 2018
- [j14]Se-Kyu Oh, Byung Jun Park, Jong Min Lee:
Point-to-point iterative learning model predictive control. Autom. 89: 135-143 (2018) - [j13]Dong Hwi Jeong, Jong Min Lee:
Enhancement of modifier adaptation scheme via feedforward decision maker using historical disturbance data and deep machine learning. Comput. Chem. Eng. 108: 31-46 (2018) - [j12]Jong Woo Kim, Go Bong Choi, Jong Min Lee:
A POMDP framework for integrated scheduling of infrastructure maintenance and inspection. Comput. Chem. Eng. 112: 239-252 (2018) - [j11]Won Je Lee, Jonggeol Na, Kyeongsu Kim, Chul-Jin Lee, Young-Geun Lee, Jong Min Lee:
NARX modeling for real-time optimization of air and gas compression systems in chemical processes. Comput. Chem. Eng. 115: 262-274 (2018) - [j10]Seongeon Park, Jonggeol Na, Minjun Kim, Jong Min Lee:
Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics. Comput. Chem. Eng. 119: 25-37 (2018) - 2016
- [j9]Yeonsoo Kim, Shin Je Lee, Taekyoon Park, Gibaek Lee, Jung Chul Suh, Jong Min Lee:
Robust leak detection and its localization using interval estimation for water distribution network. Comput. Chem. Eng. 92: 1-17 (2016) - [j8]Se-Kyu Oh, Jong Min Lee:
Iterative learning model predictive control for constrained multivariable control of batch processes. Comput. Chem. Eng. 93: 284-292 (2016) - 2012
- [j7]Yu Yang, Jong Min Lee:
A tighter cut generation strategy for acceleration of Benders decomposition. Comput. Chem. Eng. 44: 84-93 (2012) - 2010
- [j6]Yu Yang, Jong Min Lee:
Probabilistic modeling and dynamic optimization for performance improvement and risk management of plant-wide operation. Comput. Chem. Eng. 34(4): 567-579 (2010) - 2008
- [j5]Jong Min Lee, Erwin P. Gianchandani, James A. Eddy, Jason A. Papin:
Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks. PLoS Comput. Biol. 4(5) (2008) - 2006
- [j4]Jong Min Lee, Erwin P. Gianchandani, Jason A. Papin:
Flux balance analysis in the era of metabolomics. Briefings Bioinform. 7(2): 140-150 (2006) - [j3]Jay H. Lee, Jong Min Lee:
Approximate dynamic programming based approach to process control and scheduling. Comput. Chem. Eng. 30(10-12): 1603-1618 (2006) - 2005
- [j2]Jong Min Lee, Jay H. Lee:
Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes. Autom. 41(7): 1281-1288 (2005) - 2004
- [j1]Thidarat Tosukhowong, Jong Min Lee, Jay H. Lee, Joseph Lu:
An introduction to a dynamic plant-wide optimization strategy for an integrated plant. Comput. Chem. Eng. 29(1): 199-208 (2004)
Informal and Other Publications
- 2024
- [i4]Nathan P. Lawrence, Seshu Kumar Damarla, Jong Woo Kim, Aditya Tulsyan, Faraz Amjad, Kai Wang, Benoît Chachuat, Jong Min Lee, Biao Huang, R. Bhushan Gopaluni:
Machine learning for industrial sensing and control: A survey and practical perspective. CoRR abs/2401.13836 (2024) - 2022
- [i3]R. Bhushan Gopaluni, Aditya Tulsyan, Benoît Chachuat, Biao Huang, Jong Min Lee, Faraz Amjad, Seshu Kumar Damarla, Jong Woo Kim, Nathan P. Lawrence:
Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. CoRR abs/2209.11123 (2022) - 2020
- [i2]Sang Hwan Son, Jong Woo Kim, Tae Hoon Oh, Jong Min Lee:
Model-plant mismatch learning offset-free model predictive control. CoRR abs/2012.02753 (2020) - [i1]Sang Hwan Son, Se-Kyu Oh, Byung Jun Park, Min Jun Song, Jong Min Lee:
Idle speed control with low-complexity offset-free explicit model predictive control in presence of system delay. CoRR abs/2012.02859 (2020)
Coauthor Index
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