| Artificial intelligence and cyber-physical systems: A review and perspectives for the future in the chemical industry LMC Oliveira, R Dias, CM Rebello, MAF Martins, AE Rodrigues, ... AI 2 (3), 27, 2021 | 34 | 2021 |
| A novel standpoint of Pressure Swing Adsorption processes multi-objective optimization: An approach based on feasible operation region mapping CM Rebello, MAF Martins, AE Rodrigues, JM Loureiro, AM Ribeiro, ... Chemical Engineering Research and Design 178, 590-601, 2022 | 19 | 2022 |
| From an optimal point to an optimal region: A novel methodology for optimization of multimodal constrained problems and a novel constrained sliding particle swarm optimization … CM Rebello, MAF Martins, JM Loureiro, AE Rodrigues, AM Ribeiro, ... Mathematics 9 (15), 1808, 2021 | 15 | 2021 |
| A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization IBR Nogueira, ROM Dias, CM Rebello, EA Costa, VV Santana, ... Chemical Engineering Research and Design 180, 243-253, 2022 | 14 | 2022 |
| From a Pareto front to Pareto regions: A novel standpoint for multiobjective optimization CM Rebello, MAF Martins, DD Santana, AE Rodrigues, JM Loureiro, ... Mathematics 9 (24), 3152, 2021 | 14 | 2021 |
| Machine learning-based dynamic modeling for process engineering applications: a guideline for simulation and prediction from perceptron to deep learning CM Rebello, PH Marrocos, EA Costa, VV Santana, AE Rodrigues, ... Processes 10 (2), 250, 2022 | 13 | 2022 |
| Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: a systematic scientific machine learning approach VV Santana, E Costa, CM Rebello, AM Ribeiro, C Rackauckas, ... Chemical Engineering Science 282, 119223, 2023 | 12 | 2023 |
| A reinforcement learning framework to discover natural flavor molecules LP Queiroz, CM Rebello, EA Costa, VV Santana, BCL Rodrigues, ... Foods 12 (6), 1147, 2023 | 12 | 2023 |
| Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance EA Costa, CM Rebello, L Schnitman, JM Loureiro, AM Ribeiro, ... Engineering Applications of Artificial Intelligence 127, 107364, 2024 | 11 | 2024 |
| Transfer Learning Approach to Develop Natural Molecules with Specific Flavor Requirements LP Queiroz, CM Rebello, EA Costa, VV Santana, BCL Rodrigues, ... Industrial & Engineering Chemistry Research 62 (23), 9062-9076, 2023 | 11 | 2023 |
| Augmented Reality for Chemical Engineering Education CM Rebello, GF Deiró, HK Knuutila, LC de Souza Moreira, IBR Nogueira Education for Chemical Engineers, 2024 | 9 | 2024 |
| Improved modeling of crystallization processes by Universal Differential Equations FARD Lima, CM Rebello, EA Costa, VV Santana, MGF de Moares, ... Chemical Engineering Research and Design 200, 538-549, 2023 | 8 | 2023 |
| Generating flavor molecules using scientific machine learning LP Queiroz, CM Rebello, EA Costa, VV Santana, BCL Rodrigues, ... ACS omega 8 (12), 10875-10887, 2023 | 8 | 2023 |
| Optimizing CO2 capture in pressure swing adsorption units: A deep neural network approach with optimality evaluation and operating maps for decision-making CM Rebello, IBR Nogueira Separation and Purification Technology 340, 126811, 2024 | 6 | 2024 |
| PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction VV Santana, CM Rebello, LP Queiroz, AM Ribeiro, N Shardt, ... Chemical Engineering Science 286, 119623, 2024 | 6 | 2024 |
| Mapping uncertainties of soft-sensors based on deep feedforward neural networks through a novel monte carlo uncertainties training process EA Costa, CM Rebello, VV Santana, AE Rodrigues, AM Ribeiro, ... Processes 10 (2), 409, 2022 | 6 | 2022 |
| A robust learning methodology for uncertainty-aware scientific machine learning models EA Costa, CM Rebello, M Fontana, L Schnitman, IBR Nogueira Mathematics 11 (1), 74, 2022 | 5 | 2022 |
| Bio-inspired algorithms in the optimisation of wireless sensor networks J Matos, CM Rebello, EA Costa, LP Queiroz, MJB Regufe, IBR Nogueira arXiv preprint arXiv:2210.04700, 2022 | 5 | 2022 |
| Harnessing graph neural networks to craft fragrances based on consumer feedback BCL Rodrigues, VV Santana, LP Queiroz, CM Rebello Computers & Chemical Engineering 185, 108674, 2024 | 4 | 2024 |
| An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network EA Costa, C de Menezes Rebello, VV Santana, G Reges, ... Heliyon 10 (2), 2024 | 4 | 2024 |
Idelfonso Bessa dos Reis NogueiraAssociate Professor at Norwegian University of Science and TechnologyVerified email at ntnu.no