| Machine learning for biochemical engineering: A review M Mowbray, T Savage, C Wu, Z Song, BA Cho, EA Del Rio-Chanona, ... Biochemical Engineering Journal 172, 108054, 2021 | 106 | 2021 |
| Industrial data science–a review of machine learning applications for chemical and process industries M Mowbray, M Vallerio, C Perez-Galvan, D Zhang, ADR Chanona, ... Reaction Chemistry & Engineering 7 (7), 1471-1509, 2022 | 51 | 2022 |
| Constrained model-free reinforcement learning for process optimization E Pan, P Petsagkourakis, M Mowbray, D Zhang, EA del Rio-Chanona Computers & Chemical Engineering 154, 107462, 2021 | 36 | 2021 |
| Using process data to generate an optimal control policy via apprenticeship and reinforcement learning M Mowbray, R Smith, EA Del Rio‐Chanona, D Zhang AIChE Journal 67 (9), e17306, 2021 | 31 | 2021 |
| Safe chance constrained reinforcement learning for batch process control M Mowbray, P Petsagkourakis, EA del Rio-Chanona, D Zhang Computers & chemical engineering 157, 107630, 2022 | 29 | 2022 |
| Probabilistic machine learning based soft-sensors for product quality prediction in batch processes M Mowbray, H Kay, S Kay, PC Caetano, A Hicks, C Mendoza, A Lane, ... Chemometrics and Intelligent Laboratory Systems 228, 104616, 2022 | 16 | 2022 |
| Integrating process design and control using reinforcement learning S Sachio, M Mowbray, MM Papathanasiou, EA del Rio-Chanona, ... Chemical Engineering Research and Design 183, 160-169, 2022 | 14 | 2022 |
| Development and characterization of a probe device toward intracranial spectroscopy of traumatic brain injury M Mowbray, C Banbury, JJS Rickard, DJ Davies, ... ACS biomaterials science & engineering 7 (3), 1252-1262, 2021 | 11 | 2021 |
| A reinforcement learning‐based hybrid modeling framework for bioprocess kinetics identification MR Mowbray, C Wu, AW Rogers, EAD Rio‐Chanona, D Zhang Biotechnology and Bioengineering 120 (1), 154-168, 2023 | 10 | 2023 |
| A two-step multivariate statistical learning approach for batch process soft sensing A Hicks, M Johnston, M Mowbray, M Barton, A Lane, C Mendoza, P Martin, ... Digital Chemical Engineering 1, 100003, 2021 | 10 | 2021 |
| Distributional reinforcement learning for inventory management in multi-echelon supply chains G Wu, MÁ de Carvalho Servia, M Mowbray Digital Chemical Engineering 6, 100073, 2023 | 9 | 2023 |
| Integrating autoencoder and heteroscedastic noise neural networks for the batch process soft-sensor design S Kay, H Kay, M Mowbray, A Lane, C Mendoza, P Martin, D Zhang Industrial & Engineering Chemistry Research 61 (36), 13559-13569, 2022 | 9 | 2022 |
| Distributional reinforcement learning for scheduling of chemical production processes M Mowbray, D Zhang, EADR Chanona arXiv preprint arXiv:2203.00636, 2022 | 7 | 2022 |
| Model-free safe reinforcement learning for chemical processes using Gaussian processes T Savage, D Zhang, M Mowbray, EADR Chanona IFAC-PapersOnLine 54 (3), 504-509, 2021 | 5 | 2021 |
| Constrained Q-Learning for Batch Process Optimization E Pan, P Petsagkourakis, M Mowbray, D Zhang, A del Rio-Chanona Challenges of Real-World Reinforcement Learning Workshop at the 34th …, 2021 | 4 | 2021 |
| An analysis of multi-agent reinforcement learning for decentralized inventory control systems M Mousa, D van de Berg, N Kotecha, EA del Rio-Chanona, M Mowbray arXiv preprint arXiv:2307.11432, 2023 | 2 | 2023 |
| Machine learning for viscoelastic constitutive model identification and parameterisation using Large Amplitude Oscillatory Shear TP John, M Mowbray, A Alalwyat, M Vousvoukis, P Martin, A Kowalski, ... Chemical Engineering Science, 120075, 2024 | 1 | 2024 |
| Integrating transfer learning within data-driven soft sensor design to accelerate product quality control S Kay, H Kay, M Mowbray, A Lane, C Mendoza, P Martin, D Zhang Digital Chemical Engineering 10, 100142, 2024 | | 2024 |
| Constructing a Symbolic Regression-Based Interpretable Soft Sensor for Industrial Data Analytics and Product Quality Control H Kay, S Kay, M Mowbray, A Lane, C Mendoza, P Martin, D Zhang Industrial & Engineering Chemistry Research, 2024 | | 2024 |
| Constructing Time-varying and History-dependent Kinetic Models Via Reinforcement Learning M Mowbray, EA Del Rio Chanona, D Zhang | | 2023 |
Dongda ZhangUniversity Lecturer, School of Chemical Engineering and Analytical Science, University of ManchesterDirección de correo verificada de manchester.ac.uk
