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Carine de Menezes Rebello

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Carine de Menezes Rebello

Researcher
Department of Chemical Engineering
Faculty of Natural Sciences

carine.m.rebello@ntnu.no
ResearchGate Scopus Google Scholar
About Publications Teaching Outreach

About

I work at the intersection of process systems engineering, optimisation, machine learning, and control, with a strong focus on applications in the chemical process industry. 

My research activities span topics such as:

  • Process Systems Engineering and optimisation of continuous and batch processes;
  • Multi-objective and robust optimisation, with an emphasis on mapping feasible operating regions and supporting decision-making in industrial systems;
  • Scientific machine learning and hybrid modelling (phenomenological models combined with AI) for different processes;
  • Development of digital twins and cyber-physical systems with online learning, uncertainty assessment, and autonomous decision-making capabilities;
  • Application of deep learning, graph neural networks, and transfer learning to non-conventional problems such as fragrance design, discovery of molecules, and prediction of physicochemical properties;
  • Use of augmented reality in chemical engineering education and in broader digital transformation and process visualisation contexts.

    These topics are closely aligned with the vision of Industry 5.0, where advanced digital technologies are combined with human expertise to create more resilient, intelligent, and efficients.

Competencies

  • AI solutions
  • Artificial intelligence applications
  • Digital twins
  • Hybrid models
  • Process control
  • Process optimization
  • Process system engineering

Publications

  I have published over 35 manuscripts, garnering 419 citations, with an h-index of 15 (source: Google Scholar).

List of selected publications:

  • Chronological
  • By category
  • All publications registered in NVA

2025

  • Lima, Fernando Arrais Romero Dias; Moraes, Marcellus G.F. de; Rebello, Carine de Menezes; Barreto, Amaro G.; Secchi, Argimiro R.; Souza, Maurício B. de. (2025) Interpretable and uncertainty-aware machine learning for trustworthy prediction in batch crystallization. Chemical Engineering and Processing
    Academic article
  • Voltolini, Leonardo; Lima, Fernando Arrais Romero Dias; Rebello, Carine de Menezes; Itabaiana, Ivaldo; Nogueira, Idelfonso B. R.; Secchi, Argimiro Resende. (2025) Machine learning framework to predict product distribution of lignocellulosic biomass pyrolysis. Bioresource Technology
    Academic article
  • Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2025) Digital twins in chemical engineering: An integrated framework for identification, implementation, online learning, and uncertainty assessment. Computers and Chemical Engineering
    Academic article

2024

  • Santana, Vinicius; Rebello, Carine Menezes; Queiroz, Luana P.; Ribeiro, Ana Mafalda; Shardt, Nadia; Nogueira, Idelfonso B. R.. (2024) PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction. Chemical Engineering Science (CES)
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine Menezes; Schnitman, Leizer; Loureiro, José Miguel; Ribeiro, Ana Mafalda; Nogueira, Idelfonso B. R.. (2024) Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance. Engineering Applications of Artificial Intelligence
    Academic article
  • Rebello, Carine de Menezes; Deiró, Gabriela Fontes; Knuutila, Hanna Katariina; Moreira, Lorena Claudia de Souza; Nogueira, Idelfonso B. R.. (2024) Augmented reality for chemical engineering education. Education for Chemical Engineers
    Academic article
  • Moreira, Lorena Claudia de Souza; Rebello, Carine de Menezes; Costa, Erbet Almeida; Sánchez, Antonio Santos; Ribeiro, Lucília S.; Nogueira, Idelfonso B. R.. (2024) Digital Transformation in the Chemical Industry: The Potential of Augmented Reality and Digital Twin. Applied Sciences
    Academic literature review
  • Rebello, Carine de Menezes; Costa, Erbet Almeida; Sánchez, Antonio Santos; Vides, Fredy; Nogueira, Idelfonso B. R.. (2024) Assuring optimality in surrogate-based optimization: A novel theorem and its practical implementation in pressure swing adsorption optimization. Canadian Journal of Chemical Engineering
    Academic article
  • Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2024) Optimizing CO2 capture in pressure swing adsorption units: A deep neural network approach with optimality evaluation and operating maps for decision-making. Separation and Purification Technology
    Academic article
  • Rebello, Carine de Menezes; Costa, Erbet Almeida; Fontana, Marcio; Schnitman, Leizer; Nogueira, Idelfonso B. R.. (2024) Interpretable Scientific Machine Learning Approach for Correcting Phenomenological Models: Methodology Validation on an ESP Prototype. Industrial & Engineering Chemistry Research
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine de Menezes; Santana, Vinicius Viena; Nogueira, Idelfonso B. R.. (2024) Machine learning multi-step-ahead modelling with uncertainty assessment. IFAC-PapersOnLine
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine Menezes; Santana, Vinicius Viena; Reges, Galdir; Silva, Tiago de Oliveira; Abreu, Odilon Santana Luiz de. (2024) An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network. Heliyon
    Academic article
  • Rodrigues, Bruno; Santana, Vinicius Viena; Queiroz, Luana P.; Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2024) Harnessing graph neural networks to craft fragrances based on consumer feedback. Computers and Chemical Engineering
    Academic article

2023

  • Queiroz, Luana P.; Rebello, Carine Menezes; Costa, Erbet Almeida; Santana, Vinícius V.; Rodrigues, Bruno C. L.; Rodrigues, Alírio E.. (2023) Transfer Learning Approach to Develop Natural Molecules with Specific Flavor Requirements. Industrial & Engineering Chemistry Research
    Academic article
  • Lima, Fernando; Rebello, Carine Menezes; Costa, Erbet Almeida; Santana, Vinicius; Moares, Marcellus; Barreto, Amaro. (2023) Improved modeling of crystallization processes by Universal Differential Equations. Chemical engineering research & design
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine de Menezes; Santana, Vinicius Viena; Nogueira, Idelfonso B. R.. (2023) Physics-informed neural network uncertainty assessment through Bayesian inference. IFAC-PapersOnLine
    Academic article
  • Santana, Vinicius V.; Costa, Erbet Almeida; Rebello, Carine Menezes; Ribeiro, Ana Mafalda; Rackauckas, Christopher; Nogueira, Idelfonso B. R.. (2023) Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach. Chemical Engineering Science (CES)
    Academic article

Journal publications

  • Lima, Fernando Arrais Romero Dias; Moraes, Marcellus G.F. de; Rebello, Carine de Menezes; Barreto, Amaro G.; Secchi, Argimiro R.; Souza, Maurício B. de. (2025) Interpretable and uncertainty-aware machine learning for trustworthy prediction in batch crystallization. Chemical Engineering and Processing
    Academic article
  • Voltolini, Leonardo; Lima, Fernando Arrais Romero Dias; Rebello, Carine de Menezes; Itabaiana, Ivaldo; Nogueira, Idelfonso B. R.; Secchi, Argimiro Resende. (2025) Machine learning framework to predict product distribution of lignocellulosic biomass pyrolysis. Bioresource Technology
    Academic article
  • Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2025) Digital twins in chemical engineering: An integrated framework for identification, implementation, online learning, and uncertainty assessment. Computers and Chemical Engineering
    Academic article
  • Santana, Vinicius; Rebello, Carine Menezes; Queiroz, Luana P.; Ribeiro, Ana Mafalda; Shardt, Nadia; Nogueira, Idelfonso B. R.. (2024) PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction. Chemical Engineering Science (CES)
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine Menezes; Schnitman, Leizer; Loureiro, José Miguel; Ribeiro, Ana Mafalda; Nogueira, Idelfonso B. R.. (2024) Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance. Engineering Applications of Artificial Intelligence
    Academic article
  • Rebello, Carine de Menezes; Deiró, Gabriela Fontes; Knuutila, Hanna Katariina; Moreira, Lorena Claudia de Souza; Nogueira, Idelfonso B. R.. (2024) Augmented reality for chemical engineering education. Education for Chemical Engineers
    Academic article
  • Moreira, Lorena Claudia de Souza; Rebello, Carine de Menezes; Costa, Erbet Almeida; Sánchez, Antonio Santos; Ribeiro, Lucília S.; Nogueira, Idelfonso B. R.. (2024) Digital Transformation in the Chemical Industry: The Potential of Augmented Reality and Digital Twin. Applied Sciences
    Academic literature review
  • Rebello, Carine de Menezes; Costa, Erbet Almeida; Sánchez, Antonio Santos; Vides, Fredy; Nogueira, Idelfonso B. R.. (2024) Assuring optimality in surrogate-based optimization: A novel theorem and its practical implementation in pressure swing adsorption optimization. Canadian Journal of Chemical Engineering
    Academic article
  • Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2024) Optimizing CO2 capture in pressure swing adsorption units: A deep neural network approach with optimality evaluation and operating maps for decision-making. Separation and Purification Technology
    Academic article
  • Rebello, Carine de Menezes; Costa, Erbet Almeida; Fontana, Marcio; Schnitman, Leizer; Nogueira, Idelfonso B. R.. (2024) Interpretable Scientific Machine Learning Approach for Correcting Phenomenological Models: Methodology Validation on an ESP Prototype. Industrial & Engineering Chemistry Research
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine de Menezes; Santana, Vinicius Viena; Nogueira, Idelfonso B. R.. (2024) Machine learning multi-step-ahead modelling with uncertainty assessment. IFAC-PapersOnLine
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine Menezes; Santana, Vinicius Viena; Reges, Galdir; Silva, Tiago de Oliveira; Abreu, Odilon Santana Luiz de. (2024) An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network. Heliyon
    Academic article
  • Rodrigues, Bruno; Santana, Vinicius Viena; Queiroz, Luana P.; Rebello, Carine de Menezes; Nogueira, Idelfonso B. R.. (2024) Harnessing graph neural networks to craft fragrances based on consumer feedback. Computers and Chemical Engineering
    Academic article
  • Queiroz, Luana P.; Rebello, Carine Menezes; Costa, Erbet Almeida; Santana, Vinícius V.; Rodrigues, Bruno C. L.; Rodrigues, Alírio E.. (2023) Transfer Learning Approach to Develop Natural Molecules with Specific Flavor Requirements. Industrial & Engineering Chemistry Research
    Academic article
  • Lima, Fernando; Rebello, Carine Menezes; Costa, Erbet Almeida; Santana, Vinicius; Moares, Marcellus; Barreto, Amaro. (2023) Improved modeling of crystallization processes by Universal Differential Equations. Chemical engineering research & design
    Academic article
  • Costa, Erbet Almeida; Rebello, Carine de Menezes; Santana, Vinicius Viena; Nogueira, Idelfonso B. R.. (2023) Physics-informed neural network uncertainty assessment through Bayesian inference. IFAC-PapersOnLine
    Academic article
  • Santana, Vinicius V.; Costa, Erbet Almeida; Rebello, Carine Menezes; Ribeiro, Ana Mafalda; Rackauckas, Christopher; Nogueira, Idelfonso B. R.. (2023) Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach. Chemical Engineering Science (CES)
    Academic article

Teaching

Supervision

Regarding 2023 to 2025:

  • Jenny Steen - Hansen (Co-Supervisor);
  • Ane-Kristine Kjølner (Co-Supervisor);
  • Pelle Thomsen (CO-Supervisor).

Outreach

2025

  • Academic lecture
    Moreira, Lorena Claudia de Souza; Rebello, Carine de Menezes; Knuutila, Hanna Katariina; Nogueira, Idelfonso Bessa Dos Reis. (2025) Enhancing Chemical Engineering Education through Augmented Reality Applications. Læringsfestivalen , Trondheim 2025-05-19 - 2025-05-20

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