Dongda Zhang

According to our database, Dongda Zhang authored at least 19 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

From Feasible to Practical: Pareto-Optimal Synthesis Planning.

Friedrich Hastedt, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, May, 2026

Improving Fidelity and Diversity in Chemical Language Transformers for Inverse Molecular Design.

Alexander W. Rogers, Ruediger Zillmer, Amanda Lane, Adam Kowalski, Dongda Zhang

J. Chem. Inf. Model., 2026

2025

MolPrice: assessing synthetic accessibility of molecules based on market value.

Friedrich Hastedt, Klaus Hellgardt, Sophia N. Yaliraki, Dongda Zhang, Antonio del Rio-Chanona

J. Cheminformatics, December, 2025

Constraint-Guided Symbolic Regression for Data-Efficient Kinetic Model Discovery.

Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, King Kuok Hii, Klaus Hellgardt, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, July, 2025

Reinforcement learning for robust dynamic metabolic control.

Sebastián Espinel-Ríos, River Walser, Dongda Zhang

CoRR, April, 2025

Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses.

Sebastián Espinel-Ríos, José L. Avalos, Ehecatl Antonio del Rio-Chanona, Dongda Zhang

Comput. Chem. Eng., 2025

2024

Enhancing reinforcement learning for population setpoint tracking in co-cultures.

Sebastián Espinel-Ríos, Joyce Qiaoxi Mo, Dongda Zhang, Ehecatl Antonio del Rio-Chanona, José L. Avalos

CoRR, 2024

Simplest Mechanism Builder Algorithm (SiMBA): An Automated Microkinetic Model Discovery Tool.

Miguel Ángel de Carvalho Servia, King Kuok Hii, Klaus Hellgardt, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, 2024

Integrating knowledge-guided symbolic regression and model-based design of experiments to automate process flow diagram development.

Alexander W. Rogers, Amanda Lane, Cesar Mendoza, Simon Watson, Adam Kowalski, Philip Martin, Dongda Zhang

CoRR, 2024

2023

The Automated Discovery of Kinetic Rate Models - Methodological Frameworks.

Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt, King Kuok Hii, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, 2023

2022

Distributional Reinforcement Learning for Scheduling of Chemical Production Processes.

Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, 2022

Safe chance constrained reinforcement learning for batch process control.

Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Dongda Zhang

Comput. Chem. Eng., 2022

2021

Safe Chance Constrained Reinforcement Learning for Batch Process Control.

Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona, Robin Smith, Dongda Zhang

CoRR, 2021

Constrained model-free reinforcement learning for process optimization.

Elton Pan, Panagiotis Petsagkourakis, Max Mowbray, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

Comput. Chem. Eng., 2021

2020

Chance Constrained Policy Optimization for Process Control and Optimization.

Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, 2020

Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty.

Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

CoRR, 2020

Reinforcement learning for batch bioprocess optimization.

Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

Comput. Chem. Eng., 2020

Stochastic data-driven model predictive control using gaussian processes.

Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona

Comput. Chem. Eng., 2020

2018

Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes.

Eric Bradford, Artur M. Schweidtmann, Dongda Zhang, Keju Jing, Ehecatl Antonio del Rio-Chanona

Comput. Chem. Eng., 2018