Ehecatl Antonio del Rio-Chanona

65 papers C 1Journal 61Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A survey and tutorial of reinforcement learning methods in Process Systems Engineering. Comput. Chem. Eng. Maximilian Bloor, Max Mowbray, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2026	J	`jnl`	PC-Gym: Benchmark environments for process control problems. Comput. Chem. Eng. Maximilian Bloor, José Torraca, Ilya Orson Sandoval, Akhil Ahmed, Martha White, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2026	J	`jnl`	Reinforcement learning meets bioprocess control through behavior cloning: Real-world deployment in an industrial photobioreactor. Eng. Appl. Artif. Intell. Juan D. Gil, Ehecatl Antonio del Rio-Chanona, José Luis Guzmán, Manuel Berenguel
2025	J	`jnl`	ARRTOC: Adversarially Robust Real-Time Optimization and Control. Comput. Chem. Eng. Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2025	J	`jnl`	Constraint-Guided Symbolic Regression for Data-Efficient Kinetic Model Discovery. CoRR Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, King Kuok Hii, Klaus Hellgardt, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2025	J	`jnl`	Data-driven Koopman MPC using Mixed Stochastic-Deterministic Tubes. CoRR Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2025	J	`jnl`	Deep Kernel Bayesian Optimisation for Closed-Loop Electrode Microstructure Design with User-Defined Properties based on GANs. CoRR Andrea Gayon-Lombardo, Ehecatl Antonio del Rio-Chanona, Catalina A. Pino-Munoz, Nigel P. Brandon
2025	J	`jnl`	Hierarchical RL-MPC for Demand Response Scheduling. CoRR Maximilian Bloor, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2025	J	`jnl`	MORSE: Multi-Objective Reinforcement Learning via Strategy Evolution for Supply Chain Optimization. CoRR Niki Kotecha, Ehecatl Antonio del Rio-Chanona
2025	J	`jnl`	Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses. Comput. Chem. Eng. Sebastián Espinel-Ríos, José L. Avalos, Ehecatl Antonio del Rio-Chanona, Dongda Zhang
2025	J	`jnl`	Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses. CoRR Sebastián Espinel-Ríos, José L. Avalos, Ehecatl Antonio del Rio-Chanona, Dongda Zhang
2025	J	`jnl`	Reinforcement learning meets bioprocess control through behaviour cloning: Real-world deployment in an industrial photobioreactor. CoRR Juan D. Gil, Ehecatl Antonio del Rio-Chanona, José Luis Guzmán, Manuel Berenguel
2025	J	`jnl`	Survey and Tutorial of Reinforcement Learning Methods in Process Systems Engineering. CoRR Maximilian Bloor, Max Mowbray, Ehecatl Antonio del Rio-Chanona, Calvin Tsay
2024	J	`jnl`	An analysis of multi-agent reinforcement learning for decentralized inventory control systems. Comput. Chem. Eng. Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2024	J	`jnl`	Control-Informed Reinforcement Learning for Chemical Processes. CoRR Maximilian Bloor, Akhil Ahmed, Niki Kotecha, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona
2024	J	`jnl`	Enhancing reinforcement learning for population setpoint tracking in co-cultures. CoRR Sebastián Espinel-Ríos, Joyce Qiaoxi Mo, Dongda Zhang, Ehecatl Antonio del Rio-Chanona, José L. Avalos
2024	J	`jnl`	Hierarchical planning-scheduling-control - Optimality surrogates and derivative-free optimization. Comput. Chem. Eng. Damien van de Berg, Nilay Shah, Ehecatl Antonio del Rio-Chanona
2024	J	`jnl`	Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems. CoRR Tom Savage, Ehecatl Antonio del Rio-Chanona
2024	J	`jnl`	Human-algorithm collaborative Bayesian optimization for engineering systems. Comput. Chem. Eng. Tom Savage, Ehecatl Antonio del Rio-Chanona
2024	J	`jnl`	Machine learning in process systems engineering: Challenges and opportunities. Comput. Chem. Eng. Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, R. Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangöz, Ali Mesbah, Fani Boukouvala, Fernando V. Lima, Ehecatl Antonio del Rio-Chanona, Christos Georgakis
2024	J	`jnl`	PC-Gym: Benchmark Environments For Process Control Problems. CoRR Maximilian Bloor, José Torraca, Ilya Orson Sandoval, Akhil Ahmed, Martha White, Mehmet Mercangöz, Calvin Tsay, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2024	J	`jnl`	PO-SRPP: A Decentralized Pivoting Path Planning Method for Self-Reconfigurable Satellites. IEEE Trans. Ind. Electron. Dong Ye, Bo Wang, Ligang Wu, Ehecatl Antonio del Rio-Chanona, Zhaowei Sun
2024	J	`jnl`	Simplest Mechanism Builder Algorithm (SiMBA): An Automated Microkinetic Model Discovery Tool. CoRR Miguel Ángel de Carvalho Servia, King Kuok Hii, Klaus Hellgardt, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	ARRTOC: Adversarially Robust Real-Time Optimization and Control. CoRR Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2023	J	`jnl`	An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems. CoRR Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona, Max Mowbray
2023	C	`conf`	An efficient data-driven distributionally robust MPC leveraging linear programming. ACC Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2023	J	`jnl`	Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systems. CoRR Tom Savage, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	Hierarchical planning-scheduling-control - Optimality surrogates and derivative-free optimization. CoRR Damien van de Berg, Nilay Shah, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	Linearizing nonlinear dynamics using deep learning. Comput. Chem. Eng. Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2023	J	`jnl`	Machine Learning-Assisted Discovery of Novel Reactor Designs via CFD-Coupled Multi-fidelity Bayesian Optimisation. CoRR Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations. CoRR Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	Multi-fidelity data-driven design and analysis of reactor and tube simulations. Comput. Chem. Eng. Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	The Automated Discovery of Kinetic Rate Models - Methodological Frameworks. CoRR Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt, King Kuok Hii, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2023	J	`jnl`	Tube-based distributionally robust model predictive control for nonlinear process systems via linearization. Comput. Chem. Eng. Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2022	J	`jnl`	A hybrid data-driven and mechanistic model soft sensor for estimating CO Comput. Ind. Yilin Zhuang, Yixuan Liu, Akhil Ahmed, Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Colin P. Hale, Mehmet Mercangöz
2022	—	`conf`	Application of Gaussian Processes to online approximation of compressor maps for load-sharing in a compressor station. ECC Akhil Ahmed, Marta A. Zagorowska, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2022	J	`jnl`	Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors. CoRR Tom Savage, Nausheen Basha, Omar K. Matar, Ehecatl Antonio del Rio-Chanona
2022	J	`jnl`	Design and Planning of Flexible Mobile Micro-Grids Using Deep Reinforcement Learning. CoRR Cesare Caputo, Michel-Alexandre Cardin, Pudong Ge, Fei Teng, Anna Korre, Ehecatl Antonio del Rio-Chanona
2022	J	`jnl`	Distributional Reinforcement Learning for Scheduling of Chemical Production Processes. CoRR Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2022	J	`jnl`	Learning Linear Representations of Nonlinear Dynamics Using Deep Learning. CoRR Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2022	J	`jnl`	Neural ODEs as Feedback Policies for Nonlinear Optimal Control. CoRR Ilya Orson Sandoval, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona
2022	J	`jnl`	Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression. CoRR Marta A. Zagorowska, M. Degner, Lukas Ortmann, Akhil Ahmed, Saverio Bolognani, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2022	J	`jnl`	Safe chance constrained reinforcement learning for batch process control. Comput. Chem. Eng. Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Dongda Zhang
2022	J	`jnl`	Tube-based Distributionally Robust Model Predictive Control for Nonlinear Process Systems via Linearization. CoRR Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2021	J	`jnl`	A geometric deep learning approach to predict binding conformations of bioactive molecules. Nat. Mach. Intell. Oscar Méndez-Lucio, Mazen Ahmad, Ehecatl Antonio del Rio-Chanona, Jörg Kurt Wegner
2021	J	`jnl`	Application of Gaussian Processes to online approximation of compressor maps for load-sharing in a compressor station. CoRR Akhil Ahmed, Marta A. Zagorowska, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz
2021	J	`jnl`	Constrained model-free reinforcement learning for process optimization. Comput. Chem. Eng. Elton Pan, Panagiotis Petsagkourakis, Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2021	J	`jnl`	Data-driven distributionally robust MPC using the Wasserstein metric. CoRR Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2021	J	`jnl`	Hybrid Gaussian Process Modeling Applied to Economic Stochastic Model Predictive Control of Batch Processes. CoRR Eric Bradford, Lars Imsland, Marcus Reble, Ehecatl Antonio del Rio-Chanona
2021	J	`jnl`	Integrating process design and control using reinforcement learning. CoRR Steven Sachio, Max Mowbray, Maria M. Papathanasiou, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis
2021	J	`jnl`	Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation. Comput. Chem. Eng. Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat
2021	J	`jnl`	Safe Chance Constrained Reinforcement Learning for Batch Process Control. CoRR Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Robin Smith, Dongda Zhang
2021	—	`conf`	Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. CDC Panagiotis Petsagkourakis, Benoît Chachuat, Ehecatl Antonio del Rio-Chanona
2021	J	`jnl`	Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. CoRR Panagiotis Petsagkourakis, Benoît Chachuat, Ehecatl Antonio del Rio-Chanona
2020	J	`jnl`	Chance Constrained Policy Optimization for Process Control and Optimization. CoRR Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2020	J	`jnl`	Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty. CoRR Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2020	J	`jnl`	Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization. CoRR Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat
2020	J	`jnl`	Reinforcement learning for batch bioprocess optimization. Comput. Chem. Eng. Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2020	J	`jnl`	Stochastic data-driven model predictive control using gaussian processes. Comput. Chem. Eng. Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2019	—	`conf`	Nonlinear model predictive control with explicit back-offs for Gaussian process state space models. CDC Eric Bradford, Lars Imsland, Ehecatl Antonio del Rio-Chanona
2019	J	`jnl`	Reinforcement Learning for Batch Bioprocess Optimization. CoRR Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2019	J	`jnl`	Stochastic data-driven model predictive control using Gaussian processes. CoRR Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2018	J	`jnl`	Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes. Comput. Chem. Eng. Eric Bradford, Artur M. Schweidtmann, Dongda Zhang, Keju Jing, Ehecatl Antonio del Rio-Chanona
2017	J	`jnl`	On the solution of differential-algebraic equations through gradient flow embedding. Comput. Chem. Eng. Ehecatl Antonio del Rio-Chanona, Craig Bakker, Fabio Fiorelli, Michail Paraskevopoulos, Felipe Scott, Raúl Conejeros, Vassilios S. Vassiliadis
2016	J	`jnl`	Automated structure detection for distributed process optimization. Comput. Chem. Eng. Ehecatl Antonio del Rio-Chanona, Fabio Fiorelli, Vassilios S. Vassiliadis