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ORCIDEhecatl Antonio del Rio-Chanona
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2020 – today
- 2024
[j18]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:
Machine learning in process systems engineering: Challenges and opportunities. Comput. Chem. Eng. 181: 108523 (2024)- [j17]Damien van de Berg, Nilay Shah, Ehecatl Antonio del Rio-Chanona:
Hierarchical planning-scheduling-control - Optimality surrogates and derivative-free optimization. Comput. Chem. Eng. 188: 108726 (2024) - [j16]Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona, Max Mowbray:
An analysis of multi-agent reinforcement learning for decentralized inventory control systems. Comput. Chem. Eng. 188: 108783 (2024) - [j15]Tom Savage, Ehecatl Antonio del Rio-Chanona:
Human-algorithm collaborative Bayesian optimization for engineering systems. Comput. Chem. Eng. 189: 108810 (2024) - [j14]Dong Ye, Bo Wang, Ligang Wu, Ehecatl Antonio del Rio-Chanona, Zhaowei Sun:
PO-SRPP: A Decentralized Pivoting Path Planning Method for Self-Reconfigurable Satellites. IEEE Trans. Ind. Electron. 71(11): 14318-14327 (2024) - [i28]Tom Savage, Ehecatl Antonio del Rio-Chanona:
Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems. CoRR abs/2404.10949 (2024) - 2023
- [j13]Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
Linearizing nonlinear dynamics using deep learning. Comput. Chem. Eng. 170: 108104 (2023) - [j12]Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis:
Tube-based distributionally robust model predictive control for nonlinear process systems via linearization. Comput. Chem. Eng. 170: 108112 (2023) - [j11]Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona:
Multi-fidelity data-driven design and analysis of reactor and tube simulations. Comput. Chem. Eng. 179: 108410 (2023) - [c4]Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis:
An efficient data-driven distributionally robust MPC leveraging linear programming. ACC 2023: 2022-2027 - [i27]Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt, King Kuok Hii, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
The Automated Discovery of Kinetic Rate Models - Methodological Frameworks. CoRR abs/2301.11356 (2023) - [i26]Jaime Sabal Bermúdez, Antonio del Rio-Chanona, Calvin Tsay:
Distributional constrained reinforcement learning for supply chain optimization. CoRR abs/2302.01727 (2023) - [i25]Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona:
Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations. CoRR abs/2305.00710 (2023) - [i24]Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona, Max Mowbray:
An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems. CoRR abs/2307.11432 (2023) - [i23]Tom Savage, Nausheen Basha, Jonathan McDonough, Omar K. Matar, Ehecatl Antonio del Rio-Chanona:
Machine Learning-Assisted Discovery of Novel Reactor Designs via CFD-Coupled Multi-fidelity Bayesian Optimisation. CoRR abs/2308.08841 (2023) - [i22]Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
ARRTOC: Adversarially Robust Real-Time Optimization and Control. CoRR abs/2309.04386 (2023) - [i21]Damien van de Berg, Nilay Shah, Ehecatl Antonio del Rio-Chanona:
Hierarchical planning-scheduling-control - Optimality surrogates and derivative-free optimization. CoRR abs/2310.07870 (2023) - [i20]Tom Savage, Ehecatl Antonio del Rio-Chanona:
Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systems. CoRR abs/2312.02852 (2023) - 2022
- [j10]Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Dongda Zhang:
Safe chance constrained reinforcement learning for batch process control. Comput. Chem. Eng. 157: 107630 (2022) - [j9]Yilin Zhuang, Yixuan Liu, Akhil Ahmed, Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Colin P. Hale, Mehmet Mercangöz:
A hybrid data-driven and mechanistic model soft sensor for estimating CO2 concentrations for a carbon capture pilot plant. Comput. Ind. 143: 103747 (2022) - [c3]Akhil Ahmed, Marta A. Zagorowska, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
Application of Gaussian Processes to online approximation of compressor maps for load-sharing in a compressor station. ECC 2022: 205-212 - [i19]Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Distributional Reinforcement Learning for Scheduling of Chemical Production Processes. CoRR abs/2203.00636 (2022) - [i18]Akhil Ahmed, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
Learning Linear Representations of Nonlinear Dynamics Using Deep Learning. CoRR abs/2204.01064 (2022) - [i17]Ilya Orson Sandoval, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona:
Neural ODEs as Feedback Policies for Nonlinear Optimal Control. CoRR abs/2210.11245 (2022) - [i16]Tom Savage, Nausheen Basha, Omar K. Matar, Ehecatl Antonio del Rio-Chanona:
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors. CoRR abs/2210.17213 (2022) - [i15]Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis:
Tube-based Distributionally Robust Model Predictive Control for Nonlinear Process Systems via Linearization. CoRR abs/2211.14595 (2022) - [i14]Marta A. Zagorowska, M. Degner, Lukas Ortmann, Akhil Ahmed, Saverio Bolognani, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression. CoRR abs/2212.03604 (2022) - [i13]Cesare Caputo, Michel-Alexandre Cardin, Pudong Ge, Fei Teng, Anna Korre, Ehecatl Antonio del Rio-Chanona:
Design and Planning of Flexible Mobile Micro-Grids Using Deep Reinforcement Learning. CoRR abs/2212.04136 (2022) - 2021
- [j8]Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat:
Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation. Comput. Chem. Eng. 147: 107249 (2021) - [j7]Elton Pan, Panagiotis Petsagkourakis, Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Constrained model-free reinforcement learning for process optimization. Comput. Chem. Eng. 154: 107462 (2021) - [j6]Oscar Méndez-Lucio, Mazen Ahmad, Ehecatl Antonio del Rio-Chanona, Jörg Kurt Wegner:
A geometric deep learning approach to predict binding conformations of bioactive molecules. Nat. Mach. Intell. 3(12): 1033-1039 (2021) - [c2]Panagiotis Petsagkourakis, Benoît Chachuat, Ehecatl Antonio del Rio-Chanona:
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. CDC 2021: 6734-6741 - [i12]Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Robin Smith, Dongda Zhang:
Safe Chance Constrained Reinforcement Learning for Batch Process Control. CoRR abs/2104.11706 (2021) - [i11]Zhengang Zhong, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis:
Data-driven distributionally robust MPC using the Wasserstein metric. CoRR abs/2105.08414 (2021) - [i10]Steven Sachio, Max Mowbray, Maria M. Papathanasiou, Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis:
Integrating process design and control using reinforcement learning. CoRR abs/2108.05242 (2021) - [i9]Eric Bradford, Lars Imsland, Marcus Reble, Ehecatl Antonio del Rio-Chanona:
Hybrid Gaussian Process Modeling Applied to Economic Stochastic Model Predictive Control of Batch Processes. CoRR abs/2108.06430 (2021) - [i8]Panagiotis Petsagkourakis, Benoît Chachuat, Ehecatl Antonio del Rio-Chanona:
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. CoRR abs/2111.05589 (2021) - [i7]Akhil Ahmed, Marta A. Zagorowska, Ehecatl Antonio del Rio-Chanona, Mehmet Mercangöz:
Application of Gaussian Processes to online approximation of compressor maps for load-sharing in a compressor station. CoRR abs/2111.11890 (2021) - 2020
- [j5]Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Reinforcement learning for batch bioprocess optimization. Comput. Chem. Eng. 133 (2020) - [j4]Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Stochastic data-driven model predictive control using gaussian processes. Comput. Chem. Eng. 139: 106844 (2020) - [i6]Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty. CoRR abs/2006.02750 (2020) - [i5]Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Chance Constrained Policy Optimization for Process Control and Optimization. CoRR abs/2008.00030 (2020) - [i4]Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat:
Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization. CoRR abs/2009.08819 (2020) - [i3]Elton Pan, Panagiotis Petsagkourakis, Max Mowbray, Dongda Zhang, Antonio del Rio-Chanona:
Constrained Model-Free Reinforcement Learning for Process Optimization. CoRR abs/2011.07925 (2020)
2010 – 2019
- 2019
- [c1]Eric Bradford, Lars Imsland, Ehecatl Antonio del Rio-Chanona:
Nonlinear model predictive control with explicit back-offs for Gaussian process state space models. CDC 2019: 4747-4754 - [i2]Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Reinforcement Learning for Batch Bioprocess Optimization. CoRR abs/1904.07292 (2019) - [i1]Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona:
Stochastic data-driven model predictive control using Gaussian processes. CoRR abs/1908.01786 (2019) - 2018
- [j3]Eric Bradford, Artur M. Schweidtmann, Dongda Zhang, Keju Jing, Ehecatl Antonio del Rio-Chanona:
Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes. Comput. Chem. Eng. 118: 143-158 (2018) - 2017
- [j2]Ehecatl Antonio del Rio-Chanona, Craig Bakker, Fabio Fiorelli, Michail Paraskevopoulos, Felipe Scott, Raúl Conejeros, Vassilios S. Vassiliadis:
On the solution of differential-algebraic equations through gradient flow embedding. Comput. Chem. Eng. 103: 165-175 (2017) - 2016
- [j1]Ehecatl Antonio del Rio-Chanona, Fabio Fiorelli, Vassilios S. Vassiliadis:
Automated structure detection for distributed process optimization. Comput. Chem. Eng. 89: 135-148 (2016)
Coauthor Index
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last updated on 2024-09-12 03:24 CEST by the dblp team
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