Jay H. Lee

Publication Activity (10 Years)

Years Active: 1991-2024
Publications (10 Years): 47

Top Topics

Reinforcement Learning

Predictive Control

Systems Engineering

Top Venues

Comput. Chem. Eng.

Publications

Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, R. Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangöz, Ali Mesbah, Fani Boukouvala, Fernando V. Lima, Ehecatl Antonio del Rio-Chanona, Christos Georgakis
Machine learning in process systems engineering: Challenges and opportunities. Comput. Chem. Eng. 181 (2024)
Howoun Jung, Nohjin Park, Jay H. Lee
Evaluating the Efficiency and Cost-effectiveness of RPB-based CO2 Capture: A Comprehensive Approach to Simultaneous Design and Operating Condition Optimization. CoRR (2024)
Mujin Cheon, Ha-Eun Byun, Jay H. Lee
Non-myopic Bayesian optimization using model-free reinforcement learning and its application to optimization in electrochemistry. Comput. Chem. Eng. 184 (2024)
Sunwoo Kim, Joungho Park, Jay H. Lee
Multi-technology co-optimization approach for sustainable hydrogen and electricity supply chains considering variability and demand scale. CoRR (2024)
Jaewook Lee, Seongmin Heo, Jay H. Lee
Attention Mechanism for Lithium-Ion Battery Lifespan Prediction: Temporal and Cyclic Attention. CoRR (2023)
Howoun Jung, Jay H. Lee
capture process enabled by NARX-MPC using neural network. Comput. Chem. Eng. 179 (2023)
Ha-Eun Byun, Boeun Kim, Jay H. Lee
Embedding active learning in batch-to-batch optimization using reinforcement learning. Autom. 157 (2023)
Teemu J. Ikonen, Dongho Han, Jay H. Lee, Iiro Harjunkoski
Stochastic programming of energy system operations considering terminal energy storage levels. Comput. Chem. Eng. 179 (2023)
Sunwoo Kim, Seongwhan Kang, Jay H. Lee
Optimal design of offshore wind power farm in high resolution using geographical information system. Comput. Chem. Eng. 174 (2023)
Wonsuk Chung, Sunwoo Kim, Ali S. Al Hunaidy, Hasan Imran, Aqil Jamal, Jay H. Lee
Identification of sustainable carbon capture and utilization (CCU) pathways using state-task network representation. Comput. Chem. Eng. 178 (2023)
Wonsuk Chung, Woohyun Jeong, Jaeseo Lee, Junehyeok Kim, Kosan Roh, Jay H. Lee
conversion into chemicals and fuels: Gaps and opportunities in process systems engineering. Comput. Chem. Eng. 170 (2023)
Hongbum Choi, Shin Hyuk Kim, Joongmyeon Bae, Sai P. R. Katikaneni, Aqil Jamal, Aadesh Harale, Stephen N. Paglieri, Jay H. Lee
CFD analysis and scale up of a baffled membrane reactor for hydrogen production by steam methane reforming. Comput. Chem. Eng. 165 (2022)
Ashfaq Iftakher, David A. Liñán, Seyed Soheil Mansouri, Ahaduzzaman Nahid, M. M. Faruque Hasan, M. A. A. Shoukat Choudhury, Luis A. Ricardez-Sandoval, Jay H. Lee
RD-toolbox: A computer aided toolbox for integrated design and control of reactive distillation processes. Comput. Chem. Eng. 164 (2022)
Yo Sung Yoon, Woohyun Jeong, Jaeyong Kim, Mingyun Seok, Junsoo Park, Jaemin Bae, Kyungmin Lee, Jay H. Lee
Development of inferential sensor and real-time optimizer for a vacuum distillation unit by recurrent neural network modeling of time series data. Comput. Chem. Eng. 168 (2022)
Ha-Eun Byun, Boeun Kim, Jay H. Lee
Multi-step lookahead Bayesian optimization with active learning using reinforcement learning and its application to data-driven batch-to-batch optimization. Comput. Chem. Eng. 167 (2022)
Juyeong Jung, Hyun-Kyu Choi, Sang Hwan Son, Joseph Sang-Il Kwon, Jay H. Lee
Multiscale modeling of fiber deformation: Application to a batch pulp digester for model predictive control of fiber strength. Comput. Chem. Eng. 158 (2022)
Juyeong Jung, Hyun-Kyu Choi, Sang Hwan Son, Joseph Sang-Il Kwon, Jay H. Lee
Model predictive control of fiber deformation in a batch pulp digester. ACC (2022)
Shin Hyuk Kim, Jay H. Lee, Richard D. Braatz
Multi-scale fluid dynamics simulation based on MP-PIC-PBE method for PMMA suspension polymerization. Comput. Chem. Eng. 152 (2021)
Haeun Yoo, Ha-Eun Byun, Dongho Han, Jay H. Lee
Reinforcement learning for batch process control: Review and perspectives. Annu. Rev. Control. 52 (2021)
Haeun Yoo, Boeun Kim, Jong Woo Kim, Jay H. Lee
Reinforcement learning based optimal control of batch processes using Monte-Carlo deep deterministic policy gradient with phase segmentation. Comput. Chem. Eng. 144 (2021)
Nikunja Mohan Modak, Jay H. Lee, José M. Merigó
Erratum to "Forty years of computers & chemical engineering: A bibliometric analysis" [Computers & Chemical Engineering 141 (2020) 106978]. Comput. Chem. Eng. 152 (2021)
Efstratios N. Pistikopoulos, Ana Barbosa-Póvoa, Jay H. Lee, Ruth Misener, Alexander Mitsos, Gintaras V. Reklaitis, Venkat Venkatasubramanian, Fengqi You, Rafiqul Gani
. Comput. Chem. Eng. 147 (2021)
Ha-Eun Byun, Boeun Kim, Jongkoo Lim, Jay H. Lee
Multi-objective optimization of operation of lignocellulosic acetone-butanol-ethanol fermentation with ex situ butanol recovery (ESBR). Comput. Chem. Eng. 140 (2020)
Ha-Eun Byun, Boeun Kim, Jay H. Lee
Robust Dual Control of Batch Processes with Parametric Uncertainty using Proximal Policy Optimization. CDC (2020)
Shin Hyuk Kim, Jay H. Lee, Richard D. Braatz
Multi-phase particle-in-cell coupled with population balance equation (MP-PIC-PBE) method for multiscale computational fluid dynamics simulation. Comput. Chem. Eng. 134 (2020)
Howoun Jung, Dasom Im, Seongmin Heo, Boeun Kim, Jay H. Lee
capture processes. Comput. Chem. Eng. 140 (2020)
Nikunja Mohan Modak, Valeria Lobos-Ossandón, José M. Merigó, Bogdan Gabrys, Jay H. Lee
Forty years of computers & chemical engineering: A bibliometric analysis. Comput. Chem. Eng. 141 (2020)
Seongbin Ga, Sangwon Lee, Jihan Kim, Jay H. Lee
capture adsorbents. Comput. Chem. Eng. 143 (2020)
Haeun Yoo, Victor M. Zavala, Jay H. Lee
Dynamic penalty function approach for constraints handling in reinforcement learning. CoRR (2020)
Dasom Im, Howoun Jung, Jay H. Lee
Modeling, simulation and optimization of the rotating packed bed (RPB) absorber and stripper for MEA-based carbon capture. Comput. Chem. Eng. 143 (2020)
Seongwoong Bae, Shin Hyuk Kim, Jay H. Lee
An investigation into the hydrodynamics of a spinning cone column: CFD simulations by an Eulerian-Lagrangian approach. Comput. Chem. Eng. 132 (2020)
Joohyun Shin, Thomas A. Badgwell, Kuang-Hung Liu, Jay H. Lee
Reinforcement Learning - Overview of recent progress and implications for process control. Comput. Chem. Eng. 127 (2019)
Kyung Hwan Ryu, Boeun Kim, Jay H. Lee
A model-based optimization of microalgal cultivation strategies for lipid production under photoautotrophic condition. Comput. Chem. Eng. 121 (2019)
Heungjo An, Sangdo (Sam) Choi, Jay H. Lee
Integrated scheduling of vessel dispatching and port operations in the closed-loop shipping system for transporting petrochemicals. Comput. Chem. Eng. 126 (2019)
Haeun Yoo, Kosan Roh, Ali S. Al Hunaidy, Hasan Imran, Jay H. Lee
reduction. Comput. Chem. Eng. 124 (2019)
Joohyun Shin, Jay H. Lee
Multi-timescale, multi-period decision-making model development by combining reinforcement learning and mathematical programming. Comput. Chem. Eng. 121 (2019)
Seongmin Heo, Jay H. Lee
Parallel neural networks for improved nonlinear principal component analysis. Comput. Chem. Eng. 127 (2019)
Kyungseok Noh, Joohyun Shin, Jay H. Lee
An optimization based strategy for crude selection in a refinery with lube hydro-processing. Comput. Chem. Eng. 116 (2018)
Prodromos Daoutidis, Jay H. Lee, Iiro Harjunkoski, Sigurd Skogestad, Michael Baldea, Christos Georgakis
Integrating operations and control: A perspective and roadmap for future research. Comput. Chem. Eng. 115 (2018)
Boeun Kim, Jay H. Lee
Improved Parameter Estimation of Ill-Conditioned Problems. CDC (2018)
Jay H. Lee, Joohyun Shin, Matthew J. Realff
Machine learning: Overview of the recent progresses and implications for the process systems engineering field. Comput. Chem. Eng. 114 (2018)
Seongbin Ga, Hong Jang, Jay H. Lee
capture. Comput. Chem. Eng. 102 (2017)
Joohyun Shin, Jay H. Lee, Matthew J. Realff
Stochastic optimization with value function approximation for micro-grid operation. CDC (2016)
Kosan Roh, Rebecca Frauzem, Tuan B. H. Nguyen, Rafiqul Gani, Jay H. Lee
utilization processes. Comput. Chem. Eng. 91 (2016)
Hong Jang, Kwang-Ki K. Kim, Richard D. Braatz, R. Bhushan Gopaluni, Jay H. Lee
Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks. Comput. Chem. Eng. 90 (2016)
Muhammad Zaman, Hong Jang, Muhammad Rizwan, Jay H. Lee
capture plant with uncertain economic factors. Comput. Chem. Eng. 84 (2016)
Joohyun Shin, Jay H. Lee
Multi-time scale procurement planning considering multiple suppliers and uncertainty in supply and demand. Comput. Chem. Eng. 91 (2016)
Muhammad Rizwan, Muhammad Zaman, Jay H. Lee, Rafiqul Gani
Optimal processing pathway selection for microalgae-based biorefinery under uncertainty. Comput. Chem. Eng. 82 (2015)
Muhammad Zaman, Jay H. Lee
capture plant. Comput. Chem. Eng. 75 (2015)
Kevin Yeh, Craig Whittaker, Matthew J. Realff, Jay H. Lee
Two stage stochastic bilevel programming model of a pre-established timberlands supply chain with biorefinery investment interests. Comput. Chem. Eng. 73 (2015)
Kevin Yeh, Matthew J. Realff, Jay H. Lee, Craig Whittaker
Analysis and comparison of single period single level and bilevel programming representations of a pre-existing timberlands supply chain with a new biorefinery facility. Comput. Chem. Eng. 68 (2014)
Richard D. Braatz, Jay H. Lee
Special issue in Honor of Manfred Morari's 60th Birthday. Comput. Chem. Eng. 70 (2014)
Jay H. Lee
From robust model predictive control to stochastic optimal control and approximate dynamic programming: A perspective gained from a personal journey. Comput. Chem. Eng. 70 (2014)
Hong Jang, Jay H. Lee, Richard D. Braatz, Kwang Ki Kevin Kim
Fast moving horizon estimation for a two-dimensional distributed parameter system. Comput. Chem. Eng. 63 (2014)
Kwang Ki Kevin Kim, Hong Jang, R. Bhushan Gopaluni, Jay H. Lee, Richard D. Braatz
Sparse identification in chemical master equations for monomolecular reaction networks. ACC (2014)
Rakshita Agrawal, Matthew J. Realff, Jay H. Lee
MILP based value backups in partially observed Markov decision processes (POMDPs) with very large or continuous action and observation spaces. Comput. Chem. Eng. 56 (2013)
Muhammad Rizwan, Jay H. Lee, Rafiqul Gani
Optimal processing pathway for the production of biodiesel from microalgal biomass: A superstructure based approach. Comput. Chem. Eng. 58 (2013)
Seung Sohn, Tae Kim, Jay H. Lee, Sang Lee
Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth. BMC Syst. Biol. 6 (2012)
Jinkyung Kim, Matthew J. Realff, Jay H. Lee
Optimal design and global sensitivity analysis of biomass supply chain networks for biofuels under uncertainty. Comput. Chem. Eng. 35 (9) (2011)
Nikolaos E. Pratikakis, Matthew J. Realff, Jay H. Lee
Controlled exploration of state space in off-line ADP and its application to stochastic shortest path problems. Comput. Chem. Eng. 33 (12) (2009)
Wee Chin Wong, Jay H. Lee
A reinforcement learning-based scheme for adaptive optimal control of linear stochastic systems. ACC (2008)
Anshul Dubey, Matthew J. Realff, Jay H. Lee, Andreas S. Bommarius
Identifying the interacting positions of a protein using Boolean learning and support vector machines. Comput. Biol. Chem. 30 (4) (2006)
Jay H. Lee, Jong Min Lee
Approximate dynamic programming based approach to process control and scheduling. Comput. Chem. Eng. 30 (10-12) (2006)
Catalina Valencia Peroni, Niket S. Kaisare, Jay H. Lee
Optimal control of a fed-batch bioreactor using simulation-based approximate dynamic programming. IEEE Trans. Control. Syst. Technol. 13 (5) (2005)
Jong Min Lee, Jay H. Lee
Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes. Autom. 41 (7) (2005)
Thidarat Tosukhowong, Jay H. Lee
Real-time economic optimization for an integrated plant via a dynamic optimization scheme. ACC (2004)
Jaein Choi, Jay H. Lee, Matthew J. Realff
An algorithmic framework for improving heuristic solutions: Part II. A new version of the stochastic traveling salesman problem. Comput. Chem. Eng. 28 (8) (2004)
Jaein Choi, Matthew J. Realff, Jay H. Lee
Dynamic programming in a heuristically confined state space: a stochastic resource-constrained project scheduling application. Comput. Chem. Eng. 28 (6-7) (2004)
Jaein Choi, Matthew J. Realff, Jay H. Lee
An algorithmic framework for improving heuristic solutions: Part I. A deterministic discount coupon traveling salesman problem. Comput. Chem. Eng. 28 (8) (2004)
Jong Min Lee, Jay H. Lee
Empirical model based control of nonlinear processes using approximate dynamic programming. ACC (2004)
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) (2004)
Swathy Ramaswamy, Jay H. Lee
Robust forecasts and run-to-run control for processes with linear drifts. ACC (2003)
Dae Ryook Yang, Jay H. Lee
Java applet modules for undergraduate process control education. ACC (2003)
Douglas G. Robertson, Jay H. Lee
On the use of constraints in least squares estimation and control. Autom. 38 (7) (2002)
Kangwook Lee, Jay H. Lee, Mitsuko Fujiwara, David L. Ma, Richard D. Braatz
Run-to-run control of multidimensional crystal size distribution in a batch crystallizer. ACC (2002)
Yangdong Pan, ChangKyoo Yoo, Jay H. Lee, In-Beum Lee
Process monitoring of continuous processes with periodic operation patterns. ACC (2002)
Brian L. Cooley, Jay H. Lee
Control-relevant experiment design for multivariable systems described by expansions in orthonormal bases. Autom. 37 (2) (2001)
Christopher V. Rao, James B. Rawlings, Jay H. Lee
Constrained linear state estimation - a moving horizon approach. Autom. 37 (10) (2001)
Jay H. Lee, Kwang S. Lee, Won C. Kim
Model-based iterative learning control with a quadratic criterion for time-varying linear systems. Autom. 36 (5) (2000)
Jay H. Lee, Yudi Samyudia
LMI-based optimal design of test signals for control-relevant system identification. ACC (2000)
Jay H. Lee, Brian L. Cooley
Min-max predictive control techniques for a linear state-space system with a bounded set of input matrices. Autom. 36 (3) (2000)
Kwang S. Lee, Jay H. Lee
Convergence of constrained model-based predictive control for batch processes. IEEE Trans. Autom. Control. 45 (10) (2000)
Yangdong Pan, Jay H. Lee
Recursive data-based prediction and control of product quality for a batch PMMA reactor. ACC (2000)
Douglas G. Robertson, Jay H. Lee
A method for the estimation of infrequent abrupt changes in nonlinear systems. Autom. 34 (2) (1998)
Jay H. Lee, Brian L. Cooley
Optimal feedback control strategies for state-space systems with stochastic parameters. IEEE Trans. Autom. Control. 43 (10) (1998)
Jay H. Lee, Parthasarathy Kesavan, Manfred Morari
Control structure selection and robust control system design for a high-purity distillation column. IEEE Trans. Control. Syst. Technol. 5 (4) (1997)
Jay H. Lee, Zhenghong Yu
Worst-case formulations of model predictive control for systems with bounded parameters. Autom. 33 (5) (1997)
Jay H. Lee, Richard D. Braatz, Manfred Morari, Andrew K. Packard
Screening tools for robust control structure selection. Autom. 31 (2) (1995)
Jay H. Lee, Manfred Morari, Carlos E. Garcia
State-space interpretation of model predictive control. Autom. 30 (4) (1994)
Jay H. Lee, Manfred Morari
Robust measurement selection. Autom. 27 (3) (1991)