DIETI Contact person / Partner: Paolo Maresca
Abstract
Health-related analyses generate huge amounts of heterogeneous data. Obtaining knowledge from these “big data” is both challenging and promising for data-driven medicine, that can benefit from AI tools to infer models for such complex problems. The PhD research activities will include model design, optimization, and validation, applied to prospective and retrospective studies, with the support of the MS partner (including data sanitization operations, and resulting analysis and validation). The PhD student will spend at least six months abroad working under the guidance of one or both our foreign partners, University of Warwick (UK) and University of Saint Louis (US).
Objectives
Main goals include the development and application of innovative approaches to prospective and retrospective studies, aimed at modeling the complexity of infectious diseases. The approaches will be supported by AI and Big Data technologies.
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Already assigned to a PhD student of cycle XXXV