Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics. - Sebastián Espinel-Ríos; Bruno Morabito; Johannes Pohlodek; Katja Bettenbrock; Steffen Klamt; Rolf Findeisen (CoRR, 2023)

Linking intra- and extra-cellular metabolic domains via neural-network surrogates for dynamic metabolic control. - Sebastián Espinel-Ríos; José L. Avalos (CoRR, 2023)

Hybrid physics-informed metabolic cybergenetics: process rates augmented with machine-learning surrogates informed by flux balance analysis. - Sebastián Espinel-Ríos; José L. Avalos (CoRR, 2024)

Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models. - Sebastián Espinel-Ríos; Gerrich Behrendt; Jasmin Bauer; Bruno Morabito; Johannes Pohlodek; Andrea Schütze; Rolf Findeisen; Katja Bettenbrock; Steffen Klamt (CoRR, 2024)

Omics-driven hybrid dynamic modeling of bioprocesses with uncertainty estimation. - Sebastián Espinel-Ríos; José Montaño López; José L. Avalos (CoRR, 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)

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)

Reinforcement learning for robust dynamic metabolic control. - Sebastián Espinel-Ríos; River Walser; Dongda Zhang (CoRR, 2025)