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Wenbo Zhu
Wenbo Zhu
Novartis Pharma
Verified email at novartis.com
Title
Cited by
Cited by
Year
Continuous control of a polymerization system with deep reinforcement learning
Y Ma, W Zhu, MG Benton, J Romagnoli
Journal of Process Control 75, 40-47, 2019
1162019
Data mining and clustering in chemical process databases for monitoring and knowledge discovery
MC Thomas, W Zhu, JA Romagnoli
Journal of Process Control 67, 160-175, 2018
822018
Deep learning based soft sensor and its application on a pyrolysis reactor for compositions predictions of gas phase components
W Zhu, Y Ma, Y Zhou, M Benton, J Romagnoli
Computer Aided Chemical Engineering 44, 2245-2250, 2018
522018
Investigation of transfer learning for image classification and impact on training sample size
W Zhu, B Braun, LH Chiang, JA Romagnoli
Chemometrics and Intelligent Laboratory Systems 211, 104269, 2021
462021
A deep learning approach for process data visualization using t-distributed stochastic neighbor embedding
W Zhu, ZT Webb, K Mao, J Romagnoli
Industrial & Engineering Chemistry Research 58 (22), 9564-9575, 2019
402019
Adaptive k-nearest-neighbor method for process monitoring
W Zhu, W Sun, J Romagnoli
Industrial & Engineering Chemistry Research 57 (7), 2574-2586, 2018
362018
A machine learning approach to optimize shale gas supply chain networks
HI Asala, J Chebeir, W Zhu, I Gupta, AD Taleghani, J Romagnoli
SPE Annual Technical Conference and Exhibition?, D031S030R005, 2017
332017
Deep learning for pyrolysis reactor monitoring: From thermal imaging toward smart monitoring system
W Zhu, Y Ma, MG Benton, JA Romagnoli, Y Zhan
AIChE Journal 65 (2), 582-591, 2019
322019
A deep learning image-based sensor for real-time crystal size distribution characterization
V Manee, W Zhu, JA Romagnoli
Industrial & Engineering Chemistry Research 58 (51), 23175-23186, 2019
302019
Operation optimization of a cryogenic NGL recovery unit using deep learning based surrogate modeling
W Zhu, J Chebeir, JA Romagnoli
Computers & Chemical Engineering 137, 106815, 2020
292020
Online optimal feedback control of polymerization reactors: Application to polymerization of acrylamide–water–potassium persulfate (kps) system
N Ghadipasha, W Zhu, JA Romagnoli, T McAfee, T Zekoski, WF Reed
Industrial & Engineering Chemistry Research 56 (25), 7322-7335, 2017
212017
Framework design for weight-average molecular weight control in semi-batch polymerization
SD Salas, N Ghadipasha, W Zhu, T Mcafee, T Zekoski, WF Reed, ...
Control Engineering Practice 78, 12-23, 2018
182018
Generic process visualization using parametric t-SNE
W Zhu, Z Webb, X Han, K Mao, W Sun, J Romagnoli
IFAC-PapersOnLine 51 (18), 803-808, 2018
72018
Benchmark study of reinforcement learning in controlling and optimizing batch processes
W Zhu, I Castillo, Z Wang, R Rendall, LH Chiang, P Hayot, JA Romagnoli
Journal of Advanced Manufacturing and Processing 4 (2), e10113, 2022
52022
Control of a polyol process using reinforcement learning
W Zhu, R Rendall, I Castillo, Z Wang, LH Chiang, P Hayot, JA Romagnoli
IFAC-PapersOnLine 54 (3), 498-503, 2021
52021
General feature extraction for process monitoring using transfer learning approaches
W Zhu, J Zhang, J Romagnoli
Industrial & Engineering Chemistry Research 61 (15), 5202-5214, 2022
42022
Online DEKF for state estimation in semi-batch free-radical polymerization reactors
SD Salas, N Ghadipasha, W Zhu, JA Romagnoli, T Mcafee, WF Reed
Computer Aided Chemical Engineering 40, 1465-1470, 2017
42017
A Deep Learning Approach on Industrial Pyrolysis Reactor Monitoring.
W Zhu, Y Zhan, JA Romagnoli
CET Journal-Chemical Engineering Transactions 74, 2019
12019
Applying Reinforcement Learning to Control Batch Processes
W Zhu, Z Wang, I Castillo, R Rendall, L Chiang, JA Romagnoli
2020 Virtual AIChE Annual Meeting, 2020
2020
A Deep Learning Approach on Surrogate Model Optimization of a Cryogenic NGL Recovery Unit Operation
W Zhu, J Chebeir, Z Webb, J Romagnoli
Computer Aided Chemical Engineering 48, 1285-1290, 2020
2020
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