Publications

Tom Savage, Dr. Ehecatl Antonio del Rio Chanona (2024). Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems. arXiv.

Mengjia Zhu, Austin Mroz, Lingfeng Gui, Kim Jelfs, Alberto Bemporad, Dr. Ehecatl Antonio del Rio Chanona, Ye Seol Lee (2024). Discrete and mixed-variable experimental design with surrogate-based approach. ChemRxiv.

Akhil Ahmed, Dr. Ehecatl Antonio del Rio Chanona, Mehmet Mercangoz (2024). ARRTOC: Adversarially Robust Real-Time Optimization and Control. arXiv.

Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangoz, Ali Mesbah, Fani Boukouvala, Fernando V. Lima, Dr. Ehecatl Antonio del Rio Chanona, Christos Georgakis (2024). Machine learning in process systems engineering: Challenges and opportunities. Computers & Chemical Engineering.

Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, King Kuok (Mimi) Hii, Klaus Hellgardt, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona (2024). The automated discovery of kinetic rate models – methodological frameworks. Digital Discovery.

Dong Ye, Bo Wang, Ligang Wu, Dr. Ehecatl Antonio del Rio Chanona, Zhaowei Sun (2024). PO-SRPP: A Decentralized Pivoting Path Planning Method for Self-Reconfigurable Satellites. IEEE Transactions on Industrial Electronics.

Friedrich Hastedt, Rowan M. Bailey, Klaus Hellgardt, Sophia N. Yaliraki, Dr. Ehecatl Antonio del Rio Chanona, Dongda Zhang (2024). Investigating the Reliability and Interpretability of Machine Learning Frameworks for Chemical Retrosynthesis. ChemRxiv.

Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona (2023). Machine Learning and Hybrid Modelling for Reaction Engineering: Theory and Applications. Royal Society of Chemistry.

Tom Savage, Dr. Ehecatl Antonio del Rio Chanona (2023). Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systems.

Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Dr. Ehecatl Antonio del Rio Chanona (2023). Multi-fidelity data-driven design and analysis of reactor and tube simulations. Computers & Chemical Engineering.

Damien van de Berg, Nilay Shah, Dr. Ehecatl Antonio del Rio Chanona (2023). Hierarchical planning-scheduling-control -- Optimality surrogates and derivative-free optimization. arXiv.

Nausheen Basha, Tom Savage, Jonathan McDonough, Dr. Ehecatl Antonio del Rio Chanona, Omar K. Matar (2023). Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian optimisation-CFD approach. Chemical Engineering Journal.

Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Dr. Ehecatl Antonio del Rio Chanona (2023). Machine Learning-Assisted Discovery of Novel Reactor Designs. arXiv.

Marwan Mousa, damin, Niki Kotecha, Dr. Ehecatl Antonio del Rio Chanona, Max Mowbray (2023). An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems. arXiv.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2023). An efficient data-driven distributionally robust MPC leveraging linear programming. 2023 American Control Conference (ACC).

Cesare Caputo, Michel-Alexandre Cardin, Pudong Ge, Fei Teng, Anna Korre, Dr. Ehecatl Antonio del Rio Chanona (2023). Design and planning of flexible mobile Micro-Grids using Deep Reinforcement Learning. Applied Energy.

Bovinille Anye Cho, José Ángel Moreno-Cabezuelo, Lauren A. Mills, Dr. Ehecatl Antonio del Rio Chanona, David J. Lea-Smith, Dongda Zhang (2023). Integrated experimental and photo-mechanistic modelling of biomass and optical density production of fast versus slow growing model cyanobacteria. Algal Research.

Akhil Ahmed, Dr. Ehecatl Antonio del Rio Chanona, Mehmet Mercangoz (2023). Linearizing nonlinear dynamics using deep learning. Computers & Chemical Engineering.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2023). Tube-based distributionally robust model predictive control for nonlinear process systems via linearization. Computers & Chemical Engineering.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2023). Tube-based distributionally robust model predictive control for nonlinear process systems via linearization. Computers & Chemical Engineering.

Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt, King Kuok, Hii, Dongda Zhang, Ehecatl Antonio del Rio-Chanona (2023). The Automated Discovery of Kinetic Rate Models -- Methodological Frameworks. arXiv.

M. Zagorowska, M. Degner, L. Ortmann, Akhil Ahmed, S. Bolognani, Dr. Ehecatl Antonio del Rio Chanona, M. Mercangöz (2023). Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression. Journal of Process Control.

Ilya Orson Sandoval, Panagiotis Petsagkourakis, Dr. Ehecatl Antonio del Rio Chanona (2023). Neural ODEs as Feedback Policies for Nonlinear Optimal Control. IFAC-PapersOnLine.

Alexander William Rogers, Ilya Orson Sandoval, Dr. Ehecatl Antonio del Rio Chanona, Dongda Zhang (2023). Investigating physics-informed neural networks for bioprocess hybrid model construction. Computer Aided Chemical Engineering.

Eduardo Iraola, José M. Nougués, Dr. Ehecatl Antonio del Rio Chanona, Lluís Batet, Luis Sedano (2023). Hybrid data-driven and first principles monitoring applied to the Tennessee Eastman process. Computer Aided Chemical Engineering.

Luxi Yu, Dr. Ehecatl Antonio del Rio Chanona, Cleo Kontoravdi (2023). Ensemble Kalman Filter for estimation of intracellular nucleotide sugars from extracellular metabolites in monoclonal antibodies. Computer Aided Chemical Engineering.

Guoquan Wu, Miguel Ángel de Carvalho Servia, Max Mowbray (2023). Distributional reinforcement learning for inventory management in multi-echelon supply chains. Digital Chemical Engineering.

Damien van de Berg, Panagiotis Petsagkourakis, Nilay Shah, Dr. Ehecatl Antonio del Rio Chanona (2023). Data-driven coordination of subproblems in enterprise-wide optimization under organizational considerations. AIChE Journal.

Haiting Wang, Cleo Kontoravdi, Dr. Ehecatl Antonio del Rio Chanona (2023). A Hybrid Modelling Framework for Dynamic Modelling of Bioprocesses. Computer Aided Chemical Engineering.

Yilin Zhuang, Yixuan Liu, Akhil Ahmed, Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Colin P. Hale, Mehmet Mercangoz (2022). A hybrid data-driven and mechanistic model soft sensor for estimating CO2 concentrations for a carbon capture pilot plant. Computers in Industry.

Ilya Orson Sandoval, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona (2022). Neural ODEs as Feedback Policies for Nonlinear Optimal Control. arXiv.

Tom Savage, Nausheen Basha, Omar Matar, Dr. Ehecatl Antonio del Rio Chanona (2022). Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors. arXiv.

Steven Sachio, Max Mowbray, Maria M. Papathanasiou, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2022). Integrating process design and control using reinforcement learning. Chemical Engineering Research and Design.

Max Mowbray, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona (2022). Distributional Reinforcement Learning for Scheduling of Chemical Production Processes. arXiv.

Lucas Gerken-Starepravo, Xianfeng Zhu, Bovinille Anye Cho, Fernando Vega-Ramon, Oliver Pennington, Dr. Ehecatl Antonio del Rio Chanona, Keju Jing, Dongda Zhang (2022). An MIQP framework for metabolic pathways optimisation and dynamic flux analysis. Digital Chemical Engineering.

Alexander W. Rogers, Fernando Vega‐Ramon, Jiangtao Yan, Dr. Ehecatl Antonio del Rio Chanona, Keju Jing, Dongda Zhang (2022). A transfer learning approach for predictive modeling of bioprocesses using small data. Biotechnology and Bioengineering.

Ilya Stolyarov, Ilya Orson Sandoval, Panagiotis Petsagkourakis, Dr. Ehecatl Antonio del Rio Chanona (2022). Piecewise Smooth Hybrid System Identification for Model Predictive Control. Computer Aided Chemical Engineering.

Max Mowbray, Mattia Vallerio, Carlos Perez-Galvan, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona, Francisco J. Navarro-Brull (2022). Industrial data science–a review of machine learning applications for chemical and process industries. Reaction Chemistry & Engineering.

Max Mowbray, Mattia Vallerio, Carlos Perez-Galvan, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona, Francisco J. Navarro-Brull (2022). Industrial data science – a review of machine learning applications for chemical and process industries. Reaction Chemistry & Engineering.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2022). Distributionally Robust MPC for Nonlinear Systems. IFAC-PapersOnLine.

Damien van de Berg, Tom Savage, Panagiotis Petsagkourakis, Dongda Zhang, Nilay Shah, Dr. Ehecatl Antonio del Rio Chanona (2022). Data-driven optimization for process systems engineering applications. Chemical Engineering Science.

Damien van de Berg, Panagiotis Petsagkourakis, Nilay Shah, Dr. Ehecatl Antonio del Rio Chanona (2022). Data-driven coordination of expensive black-boxes. Computer Aided Chemical Engineering.

Sophie Sitter, Damien van de Berg, Max Mowbray, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2022). Convex Q-learning: Reinforcement learning through convex programming. Computer Aided Chemical Engineering.

Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona (2022). Chance Constrained Policy Optimization for Process Control and Optimization. Journal of Process Control.

Alexander W. Rogers, Fernando Vega-Ramon, Jiangtao Yan, Dr. Ehecatl Antonio del Rio Chanona, Keju Jing, Dongda Zhang (2022). A transfer learning approach for predictive modeling of bioprocesses using small data. Biotechnology and Bioengineering.

Panagiotis Petsagkourakis, Benoit Chachuat, Dr. Ehecatl Antonio del Rio Chanona (2021). Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. 2021 60th IEEE Conference on Decision and Control (CDC).

Elton Pan, Panagiotis Petsagkourakis, Max Mowbray, Dongda Zhang, Dr. Ehecatl Antonio del Rio Chanona (2021). Constrained model-free reinforcement learning for process optimization. Computers & Chemical Engineering.

Max Mowbray, Tom Savage, Chufan Wu, Ziqi Song, Bovinille Anye Cho, Dr. Ehecatl Antonio del Rio Chanona, Dongda Zhang (2021). Machine learning for biochemical engineering: A review. Biochemical Engineering Journal.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2021). Data-driven distributionally robust MPC using the Wasserstein metric. arXiv.

Damien van de Berg, Zoltán Kis, Carl Fredrik Behmer, Karnyart Samnuan, Anna K. Blakney, Cleo Kontoravdi, Robin Shattock, Nilay Shah (2021). Quality by design modelling to support rapid RNA vaccine production against emerging infectious diseases. npj Vaccines.

Bovinille Anye Cho, Miguel Ángel de Carvalho Servia, Dr. Ehecatl Antonio del Rio Chanona, Robin Smith, Dongda Zhang (2021). Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems. Biotechnology and Bioengineering.

Tom Savage, Dongda Zhang, Max Mowbray, Dr. Ehecatl Antonio del Rio Chanona (2021). Model-free safe reinforcement learning for chemical processes using Gaussian processes. IFAC-PapersOnLine.

Max Mowbray, Tom Savage, Chufan Wu, Ziqi Song, Bovinille Anye Cho, Dr. Ehecatl Antonio del Rio Chanona, Dongda Zhang (2021). Machine learning for biochemical engineering: A review. Biochemical Engineering Journal.

Zhengang Zhong, Dr. Ehecatl Antonio del Rio Chanona, Panagiotis Petsagkourakis (2021). Data-driven distributionally robust MPC using the Wasserstein metric.

Tom Savage, Fernando Almeida-Trasvina, Dr. Ehecatl Antonio del Rio Chanona, Robin Smith, Dondga Zhang (2021). An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation. AIChE Journal.

Tom Savage, Fernando Almeida-Trasvina, Dr. Ehecatl Antonio del Rio Chanona, Robin Smith, Dondga Zhang (2021). An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation. AIChE Journal.

Tom Savage, Fernando Almeida-Trasvina, Dr. Ehecatl Antonio del Rio Chanona, Robin Smith, Dongda Zhang (2020). Surrogate Modelling and Optimization for Complex Liquefied Natural Gas Refrigeration Cycles. IFAC-PapersOnLine.

Tom Savage, Dongda Zhang (2020). Superstructure Reaction Network Design for the Synthesis of Biobased Sustainable Nitrogen-Containing Polymers. Industrial & Engineering Chemistry Research.

P. Petsagkourakis, Ilya Orson Sandoval, E. Bradford, D. Zhang, Dr. Ehecatl Antonio del Rio Chanona (2020). Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty. IFAC-PapersOnLine.

Tom Savage, Hector Fernando Almeida-Trasvina, Dr. Ehecatl Antonio del Rio Chanona, Robin Smith, Dongda Zhang (2020). An adaptive data-driven modelling and optimization framework for complex chemical process design. 30th European Symposium on Computer Aided Process Engineering.

P. Petsagkourakis, Ilya Orson Sandoval, E. Bradford, D. Zhang, Dr. Ehecatl Antonio del Rio Chanona (2019). Reinforcement Learning for Batch-to-Batch Bioprocess Optimisation. 29th European Symposium on Computer Aided Process Engineering.