📚 Publications

The STAMM preprint, which provides a detailed explanation of each component, can be found here.

STAMM: Soft sensor moniToring and mAintenance framework for Machine learning Models.
Preprint, 2026
Authors: Carlos Suárez; Alexander Astudillo, Brett Metcalfe, Matthew Crowther, Jasper J. Koehorst, Esteban Castillo, Ariane Bize and David Camilo Corrales.
📄 Read paper

Although these publications do not explicitly mention the use of STAMM, the models presented in the following articles are included as part of the demo available in the model registry within the IndPenSim project.

Towards a machine learning operations (MLOps) soft sensor for real-time predictions in industrial-scale fed-batch fermentation.
Computers & Chemical Engineering, 2025
Authors: Brett Metcalfe, Juan Camilo Acosta-Pavas, Carlos Eduardo Robles-Rodriguez, George K. Georgakilas, Theodore Dalamagas, Cesar Arturo Aceves-Lara, Fayza Daboussi, Jasper J. Koehorst and David Camilo Corrales.
📄 Read paper

Soft sensors based on interpretable learners for industrial-scale fed-batch fermentation: Learning from simulations.
Computers & Chemical Engineering, 2024
Authors: Juan Camilo Acosta-Pavas, Carlos Eduardo Robles-Rodriguez, David Griol, Fayza Daboussi, Cesar Arturo Aceves-Lara and David Camilo Corrales.
📄 Read paper