AI & ML interests
Our core interest lies in developing applied Artificial Intelligence systems that address social and territorial challenges through data-driven decision-making. We focus on hybrid architectures combining Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), and Transformer-based attention models to analyze demographic, environmental, and socio-economic patterns. Findspo’s research applies Machine Learning for demographic resilience, migration forecasting, and rural revitalization, using both structured (census, remote sensing) and synthetic data generated through Generative Adversarial Networks (GANs). Our models integrate explainable AI, geospatial analysis, and swarm intelligence to simulate and predict territorial dynamics.
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