| Iron-Catalyzed N-Alkylation of Azoles via Oxidation of C−H Bond Adjacent to an Oxygen Atom S Pan, J Liu, H Li, Z Wang, X Guo, Z Li Organic letters 12 (9), 1932-1935, 2010 | 231 | 2010 |
| Recent trends on hybrid modeling for Industry 4.0 J Sansana, MN Joswiak, I Castillo, Z Wang, R Rendall, LH Chiang, ... Computers & Chemical Engineering 151, 107365, 2021 | 148 | 2021 |
| New dynamic response surface methodology for modeling nonlinear processes over semi-infinite time horizons Z Wang, C Georgakis Industrial & Engineering Chemistry Research 56 (38), 10770-10782, 2017 | 21 | 2017 |
| Integration of process knowledge and statistical learning for the dow data challenge problem SJ Qin, S Guo, Z Li, LH Chiang, I Castillo, B Braun, Z Wang Computers & Chemical Engineering 153, 107451, 2021 | 20 | 2021 |
| Monitoring chemical processes using judicious fusion of multi-rate sensor data Z Wang, L Chiang Sensors 19 (10), 2240, 2019 | 19 | 2019 |
| Towards artificial intelligence at scale in the chemical industry LH Chiang, B Braun, Z Wang, I Castillo AIChE Journal 68 (6), e17644, 2022 | 17 | 2022 |
| Data science challenges in chemical manufacturing B Braun, I Castillo, M Joswiak, Y Peng, R Rendall, A Schmidt, Z Wang, ... IFAC preprints, 2020 | 17 | 2020 |
| An in silico evaluation of data‐driven optimization of biopharmaceutical processes Z Wang, C Georgakis AIChE Journal 63 (7), 2796-2805, 2017 | 14 | 2017 |
| Sensor Fusion with Irregular Sampling and Varying Measurement Delays J Sansana, R Rendall, Z Wang, L Chiang, M Reis Industrial & Engineering Chemistry Research 59 (6), 2328-2340, 2020 | 12 | 2020 |
| Identification of Hammerstein-Weiner models for nonlinear MPC from infrequent measurements in batch processes Z Wang, C Georgakis Journal of Process Control 82, 58-69, 2019 | 12 | 2019 |
| Data-driven optimization of an industrial batch polymerization process using the design of dynamic experiments methodology C Georgakis, ST Chin, Z Wang, P Hayot, L Chiang, J Wassick, I Castillo Industrial & Engineering Chemistry Research 59 (33), 14868-14880, 2020 | 11 | 2020 |
| Sequential Parameter Estimation for Mammalian Cell Model Based on In Silico Design of Experiments Z Wang, H Sheikh, K Lee, C Georgakis Processes, 100, 2018 | 11 | 2018 |
| DRSM Model for the Optimization and Control of Batch Processes Z Wang, N Klebanov, C Georgakis IFAC-PapersOnLine 49 (7), 55-60, 2016 | 11 | 2016 |
| A dynamic response surface model for polymer grade transitions in industrial plants Z Wang, C Georgakis Industrial & Engineering Chemistry Research 58 (26), 11187-11198, 2019 | 8 | 2019 |
| On the Performance of DoDE in a class of in silico Fermentation Processes and the Impact of the Input Domain Z Wang, C Georgakis IFAC Proceedings Volumes 46 (31), 163-168, 2013 | 7 | 2013 |
| 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 | 5 | 2022 |
| Reinforcement learning-based fed-batch optimization with reaction surrogate model Y Ma, Z Wang, I Castillo, R Rendall, R Bindlish, B Ashcraft, D Bentley, ... 2021 American Control Conference (ACC), 2581-2586, 2021 | 5 | 2021 |
| 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 | 5 | 2021 |
| Multi-source Heterogeneous Data Fusion for Toxin Level Quantification E Strelet, Z Wang, Y Peng, I Castillo, R Rendall, B Braun, M Joswiak, ... IFAC-PapersOnLine 54 (3), 67-72, 2021 | 5 | 2021 |
| Hard and Soft Sensors Fusion for Process Monitoring: an Industrial Application Z Wang, L Chiang ISA 63rd Analysis Division Symposium 2018, 2018 | 5 | 2018 |
Christos GeorgakisLehigh University, MIT, Tufts University, University of Thessaloniki, Polytechnic UniversityVerified email at Tufts.edu
