Our team participated in MMR 2025 with three talks showcasing recent advances in data-driven maintenance. The presentations covered applications in the airline industry, distributed systems, and the wine sector, highlighting our interdisciplinary approach to predictive modeling, anomaly detection, and operational optimization.
At PASC 2025, I presented our work on building a trusted and scalable data infrastructure to support the Regional Field Stations Network (RCER) at Universidad Católica. The talk introduced SAVIIA—a platform that integrates scientific and operational datasets across distributed field stations using structured governance, local orchestration tools, and cloud-based pipelines. By improving data reliability, accessibility, and integration, the initiative aims to empower researchers, foster interdisciplinary collaboration, and enhance reproducibility in field-based science.
In this presentation, I summarized our work on connecting prediction and prescription in energy management for residential microgrids, using stochastic optimization and machine learning to improve decision-making under uncertainty in systems with variable generation and storage.