SCIENTIFIC EVIDENCE
The work can be reviewed before it is commissioned.
Consulting is not sustained by generic promises. It is grounded in open research on longitudinal analytics, pathways, causality, graphs, artificial intelligence and complex systems.
Publications that make the method, criteria and results reviewable.
A selection of open works. Each record retains its nature as article, thesis, preprint or working paper.
The CAPIRE framework: a unified architecture for curriculum-aware, multilevel, causal and simulation-based modelling
PREPRINT · EdArXiv↗An agent-based simulation of regularity-driven student attrition
PREPRINT · arXiv↗College dropout factors: an analysis with LightGBM and Shapley's cooperative game theory
PREPRINT · arXiv↗Student delay, dropout and university curriculum in the civil engineering major at FACET-UNT
THESIS · Zenodo↗From linear risk to emergent harm: complexity as the missing core of AI governance
WHITE PAPER · Zenodo↗WHAT THIS EVIDENCE SHOWS
Results are not merely observed: explanations are built for review.
The work documents a path from fragmented data to structural diagnosis, causal interpretation and intervention scenarios.
SCOPE AND CAUTION
The strongest empirical validation was developed in education.
Its transfer to other sectors is methodological: it identifies mechanisms, constraints and delayed effects where a dashboard is not enough.