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ORCIDJoseph Sang-Il Kwon
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2020 – today
- 2024
[c37]Niranjan Sitapure, Joseph Sang-Il Kwon:
Integrating Machine Learning in Process Control with LSTMc: A Case Study in Batch Crystallization. ACC 2024: 39-44- [c36]Niranjan Sitapure, Joseph Sang-Il Kwon:
Empowering Hybrid Models with Attention-Based Time-series Transformers: A Case Study in Batch Crystallization. ACC 2024: 62-67 - [c35]Bhavana Bhadriraju, Joseph Sang-Il Kwon, Faisal Khan:
Lyapunov-Based Model Predictive Control Using Operable Adaptive Sparse Identification of Systems (OASIS). ACC 2024: 1732-1737 - [c34]Satchit Nagpal, Joseph Sang-Il Kwon:
Enhancing Protein Crystal Purity through Adaptive Kinetic Monte Carlo Modeling and Control of Surface Morphology. ACC 2024: 4440-4445 - [c33]Silabrata Pahari, Parth Shah, Joseph Sang-Il Kwon:
Integrating Deep Neural Networks for Hybrid Modeling of Complex Chemical Processes: Estimation of Spatiotemporally Varying Parameters in Moving Boundary Problems. ACC 2024: 5370-5375 - [c32]Silabrata Pahari, Parth Shah, Chi Ho Lee, Joseph Sang-Il Kwon:
A Hybrid Modeling Framework for Catalytic Systems: Sensitivity Analysis and Estimation of Activation Energies. ACC 2024: 5376-5381 - [c31]Juhyeon Kim, Silabrata Pahari, Jiae Ryu, Mairui Zhang, Chang Geun Yoo, Joseph Sang-Il Kwon:
Adaptive Control for Lignin-First Biomass Fractionation: An Experimentally Verified Multiscale kMC Approach. ACC 2024: 5480-5485 - 2023
- [j22]Bhavana Bhadriraju, Joseph Sang-Il Kwon, Faisal Khan:
An adaptive data-driven approach for two-timescale dynamics prediction and remaining useful life estimation of Li-ion batteries. Comput. Chem. Eng. 175: 108275 (2023) - [j21]Niranjan Sitapure
, Joseph Sang-Il Kwon:
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers. Comput. Chem. Eng. 177: 108339 (2023) - [j20]Bhushan Pawar, Bhavana Bhadriraju, Faisal Khan, Joseph Sang-Il Kwon, Qingsheng Wang:
Resilience assessment of chemical processes using operable adaptive sparse identification of systems. Comput. Chem. Eng. 177: 108346 (2023) - [j19]Abhinav Narasingam, Sang Hwan Son, Joseph Sang-Il Kwon:
Data-driven feedback stabilisation of nonlinear systems: Koopman-based model predictive control. Int. J. Control 96(3): 770-781 (2023) - [c30]Mohammed Saad Faizan Bangi, Joseph Sang-Il Kwon:
Control Lyapunov-Barrier function-based predictive control using a deep hybrid model with guarantees on domain of applicability. ACC 2023: 1819-1824 - [c29]Niranjan Sitapure, Joseph Sang-Il Kwon:
Model Predictive Control of Cadmium Telluride (CdTe) Quantum Dot (QD) Crystallization. ACC 2023: 3251-3256 - [c28]Silabrata Pahari, Juhyeon Kim, Mairui Zhang, Anqi Ji, Chang Geun Yoo, Joseph Sang-Il Kwon:
Multiscale modeling, experimental validation, and optimal operation for a batch pulp digester with a novel solvent. ACC 2023: 3448-3453 - [c27]Parth Shah, Hyun-Kyu Choi, Joseph Sang-Il Kwon:
LSTM-based control of cellulose degree of polymerization in a batch pulp digester. ACC 2023: 4659-4664 - [i5]Niranjan Sitapure, Joseph Sang-Il Kwon:
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers. CoRR abs/2306.03099 (2023) - [i4]Niranjan Sitapure, Joseph Sang-Il Kwon:
Require Process Control? LSTMc is all you need! CoRR abs/2306.07510 (2023) - [i3]Niranjan Sitapure, Joseph Sang-Il Kwon:
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization. CoRR abs/2308.05749 (2023) - 2022
- [j18]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: 107640 (2022) - [j17]Kyeongseok Shin, Sang Hwan Son, Jiyoung Moon, Yeonpyeong Jo, Joseph Sang-Il Kwon, Sungwon Hwang:
Dynamic modeling and predictive control of boil-off gas generation during LNG loading. Comput. Chem. Eng. 160: 107698 (2022) - [c26]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: 2491-2496 - [c25]Bhavana Bhadriraju, Joseph Sang-Il Kwon, Faisal Khan:
Prediction and isolation of process faults using operable adaptive sparse identification of systems (OASIS) and contribution plots. ACC 2022: 3626-3631 - [c24]Mohammed Saad Faizan Bangi, Joseph Sang-Il Kwon:
Universal hybrid modeling of batch kinetics of aerobic carotenoid production using Saccharomyces Cerevisiae. ACC 2022: 3716-3721 - [c23]Pallavi Kumari, Bhavana Bhadriraju, Qingsheng Wang, Joseph Sang-Il Kwon:
Handling cyclic loops for accurate root cause diagnosis of rare events in chemical processes using modified Bayesian network. ACC 2022: 4292-4297 - [c22]Gyuyeong Hwang, Niranjan Sitapure, Jiyoung Moon, Sungwon Hwang, Joseph Sang-Il Kwon:
Mitigation of intra-cycle mechano-chemical degradation-based capacity fade in Lithium-ion batteries: Application of a model predictive controller. ACC 2022: 5282-5287 - [c21]Niranjan Sitapure, Joseph Sang-Il Kwon:
Model Predictive Control of Spray Coating of Perovskite Quantum Dots for Application in Perovskite Solar Cells. ACC 2022: 5334-5339 - 2021
- [j16]Bhavana Bhadriraju, Joseph Sang-Il Kwon, Faisal Khan:
Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS). Comput. Chem. Eng. 152: 107378 (2021) - [j15]Hyeonggeon Lee, Niranjan Sitapure, Sungwon Hwang, Joseph Sang-Il Kwon:
Multiscale modeling of dendrite formation in lithium-ion batteries. Comput. Chem. Eng. 153: 107415 (2021) - [j14]Mohammed Saad Faizan Bangi, Joseph Sang-Il Kwon:
Deep reinforcement learning control of hydraulic fracturing. Comput. Chem. Eng. 154: 107489 (2021) - [c20]Niranjan Sitapure, Robert W. Epps, Milad Abolhasani, Joseph Sang-Il Kwon:
Multiscale CFD modeling and optimal control of a continuous slug flow crystallizer for quantum dot production. ACC 2021: 1016-1021 - [c19]Dongheon Lee, Arul Jayaraman, Joseph Sang-Il Kwon:
A Hybrid Mechanistic Data-Driven Approach for Modeling Uncertain Intracellular Signaling Pathways. ACC 2021: 1903-1908 - [c18]Sang Hwan Son, Abhinav Narasingam, Joseph Sang-Il Kwon:
Integration of offset-free control framework with Koopman Lyapunov-based model predictive control. ACC 2021: 2818-2823 - [c17]Bhavana Bhadriraju, Joseph Sang-Il Kwon, Faisal Khan:
Dynamic risk-based fault prediction of chemical processes using online sparse model identification. ACC 2021: 4964-4969 - [c16]Hyun-Kyu Choi, Sang Hwan Son, Joseph Sang-Il Kwon:
Inferential model predictive control of blow-line fiber morphology in a continuous pulp digester via multiscale modeling. ACC 2021: 5043-5048 - 2020
- [j13]Mohammed Saad Faizan Bangi, Joseph Sang-Il Kwon:
Deep hybrid modeling of chemical process: Application to hydraulic fracturing. Comput. Chem. Eng. 134: 106696 (2020) - [j12]Niranjan Sitapure, Tian Qiao, Dong Hee Son, Joseph Sang-Il Kwon:
Kinetic Monte Carlo modeling of the equilibrium-based size control of CsPbBr3 perovskite quantum dots in strongly confined regime. Comput. Chem. Eng. 139: 106872 (2020) - [j11]Sang Hwan Son, Hyun-Kyu Choi, Joseph Sang-Il Kwon:
Multiscale modeling and control of pulp digester under fiber-to-fiber heterogeneity. Comput. Chem. Eng. 143: 107117 (2020) - [j10]Dongheon Lee, Arul Jayaraman, Joseph Sang-Il Kwon:
Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling. PLoS Comput. Biol. 16(12) (2020) - [c15]Prashanth Siddhamshetty, Parth Bhandakkar, Joseph Sang-Il Kwon:
Design of online pumping schedules in naturally fractured shale formations to enhance total fracture surface area. ACC 2020: 3114-3119 - [c14]Niranjan Sitapure, Tian Qiao, Dong Hee Son, Joseph Sang-Il Kwon:
Modeling and size control of CsPbBr3 perovskite quantum dots. ACC 2020: 4331-4336 - [c13]Hyun-Kyu Choi, Joseph Sang-Il Kwon:
Multiscale modeling and control of fiber length in pulp digester. ACC 2020: 4343-4348 - [c12]Abhinav Narasingam, Joseph Sang-Il Kwon:
Koopman operator-based model identification and control of hydraulic fracture propagation. ACC 2020: 4533-4538 - [c11]Dongheon Lee, Yufang Ding, Arul Jayaraman, Joseph Sang-Il Kwon:
Derivation of a Dynamic Model for Palmitate-induced NFκB Signaling Pathway through Systems Biology Approach. ACC 2020: 5028-5033 - [c10]Abhinav Narasingam, Joseph Sang-Il Kwon:
Closed-loop stabilization of nonlinear systems using Koopman Lyapunov-based model predictive control. CDC 2020: 704-709 - [i2]Abhinav Narasingam, Joseph Sang-Il Kwon:
Data-driven feedback stabilization of nonlinear systems: Koopman-based model predictive control. CoRR abs/2005.09741 (2020) - [i1]Sang Hwan Son, Abhinav Narasingam, Joseph Sang-Il Kwon:
Handling plant-model mismatch in Koopman Lyapunov-based model predictive control via offset-free control framework. CoRR abs/2010.07239 (2020)
2010 – 2019
- 2019
- [j9]Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Simultaneous measurement uncertainty reduction and proppant bank height control of hydraulic fracturing. Comput. Chem. Eng. 127: 272-281 (2019) - [j8]Hyun-Kyu Choi, Joseph Sang-Il Kwon:
Modeling and control of cell wall thickness in batch delignification. Comput. Chem. Eng. 128: 512-523 (2019) - [c9]Hyun-Kyu Choi, Joseph Sang-Il Kwon:
Multiscale modeling and model-based feedback control of pulp digester. ACC 2019: 2819-2824 - 2018
- [j7]Harwinder Singh Sidhu, Abhinav Narasingam, Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Model order reduction of nonlinear parabolic PDE systems with moving boundaries using sparse proper orthogonal decomposition: Application to hydraulic fracturing. Comput. Chem. Eng. 112: 92-100 (2018) - [j6]Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Model-based feedback control of oil production in oil-rim reservoirs under gas coning conditions. Comput. Chem. Eng. 112: 112-120 (2018) - [j5]Prashanth Siddhamshetty, Seeyub Yang, Joseph Sang-Il Kwon:
Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs. Comput. Chem. Eng. 114: 306-317 (2018) - [j4]Dongheon Lee, Alec Mohr, Joseph Sang-Il Kwon, Hung-Jen Wu:
Kinetic Monte Carlo modeling of multivalent binding of CTB proteins with GM1 receptors. Comput. Chem. Eng. 118: 283-295 (2018) - [j3]Abhinav Narasingam, Joseph Sang-Il Kwon:
Data-driven identification of interpretable reduced-order models using sparse regression. Comput. Chem. Eng. 119: 101-111 (2018) - [c8]Abhinav Narasingam, Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Identification of spatially varying geological properties in a heterogeneous reservoir using EnKF and POD based parameterization. ACC 2018: 1144-1149 - [c7]Dongheon Lee, Yufang Ding, Arul Jayaraman, Joseph Sang-Il Kwon:
Integrative Approach to Extract the Single-cell Dynamics of LPS-induced NFκB Signal Pathway through Flow Cytometry Measurements and Parameter Estimation. ACC 2018: 1975-1980 - [c6]Dongheon Lee, Akshi Singla, Hung-Jen Wu, Joseph Sang-Il Kwon:
Dynamic Modeling of Binding Kinetics Between GD1b Ganglioside and Cholera Toxin Subunit B. ACC 2018: 1999-2004 - [c5]Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Model-based feedback control of oil production in oil-rim reservoirs under gas coning conditions. ACC 2018: 2605-2610 - [c4]Caio Felippe Curitiba Marcellos, Helen Durand, Joseph Sang-Il Kwon, Amaro Gomes Barreto, Paulo Laranjeira da Cunha Lage, Maurício Bezerra de Souza Jr., Argimiro Resende Secchi, Panagiotis D. Christofides:
Model Predictive Control of Batch Enantiomer Crystallization Using Ternary Diagram Information. ACC 2018: 5927-5933 - [c3]Harwinder Singh Sidhu, Abhinav Narasingam, Joseph Sang-Il Kwon:
Model order reduction of nonlinear parabolic PDE systems with moving boundaries using sparse proper orthogonal decomposition methodology. ACC 2018: 6421-6426 - 2017
- [j2]Seeyub Yang, Prashanth Siddhamshetty, Joseph Sang-Il Kwon:
Optimal pumping schedule design to achieve a uniform proppant concentration level in hydraulic fracturing. Comput. Chem. Eng. 101: 138-147 (2017) - [j1]Abhinav Narasingam, Joseph Sang-Il Kwon:
Development of local dynamic mode decomposition with control: Application to model predictive control of hydraulic fracturing. Comput. Chem. Eng. 106: 501-511 (2017) - [c2]Prashanth Siddhamshetty, Seeyub Yang, Joseph Sang-Il Kwon:
Modeling of hydraulic fracturing and developing a new pumping schedule to achieve uniform proppant concentration. ACC 2017: 2182-2187 - 2013
- [c1]Michael Nayhouse, Joseph Sang-Il Kwon, Gerassimos Orkoulas, Panagiotis D. Christofides:
Modeling and control of protein crystal shape distribution. ACC 2013: 1896-1901
Coauthor Index
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