We aim to fuse open satellite data with local socio-environmental indicators in the Exploradores Valley, building explainable, uncertainty-aware metrics for territorial management on top of a governed, reproducible data platform.
A hybrid local–cloud platform and governance model that turns field-station data into reliable, reusable, and decision-ready assets across UC’s RCER network.
Developing a cloud-based analytical platform to optimize predictive and prescriptive maintenance across industrial systems.
We are studying data-driven prioritization models that can help hospitals manage their oncology waiting lists with application in the South Eastern Metropolitan Health Service
FONDECYT Regular project. Developing resource cost-aware scheduling solutions to optimize performance under uncertainty, with applications in astronomy and other industries.
Using operations research methodologies, we are developing new tools for observatory operations.
Using deep learning spatial-temporal graph models for seasonal forecasting of extreme temperature events.
We are combining machine learning and stochastic optimization tools to develop optimal energy management systems for fotovoltaic generation with storage.
Developing ML and decision support tools for predictive and prescriptive maintenance.