Sfida R&D: UPSCALE OF PREDICTIVE MODELS in HT Data
Sviluppo di metodi innovativi per l’analisi per dati complessi ad altissimo throughput (10^5 – 10^6 variabili, 10^3-10^4 campioni) e applicazioni alla salute umana e ambientale
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Data Mining Predittivo classificazione, regressione, feature ranking, networks
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Computational Pipelines for reproducible research: MLPY , the MAQCII-FDA project, High Performance Comp (HPC)
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Individual Based Epidemiologic Models: national pandemic models, (10^7 units), con mobility & socio-economics networks
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High Resolution Geodata (vector-raster maps, time series, well-being and socio-economic data+web): Mitris, Envirochange, ContextAware
