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

Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information. - Saurabh Malani; Tom S. Bertalan; Tianqi Cui; Jose L. Avalos; Michael Betenbaugh; Ioannis G. Kevrekidis (Comput. Chem. Eng., 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)

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)

AC-BioSD: A Biomolecular Signal Differentiator Module With Enhanced Performance. - Emmanouil Alexis; José L. Avalos; Luca Cardelli; Antonis Papachristodoulou (IEEE Control. Syst. Lett., 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)