Matteo Giuliani is an associate professor and affiliated scientist based in Milan with 12 years of experience designing data-driven strategies for integrated water resources management under climate change. He develops multi-objective optimization, control and reinforcement learning methods to support decision-making under deep uncertainty for complex, multi-actor socio-environmental systems. At Politecnico di Milano and RFF‑CMCC EIEE he combines theoretical research with applied modeling for climate adaptation and extreme events analysis, blending machine learning with evolutionary and control algorithms. His background includes international research visits (ETH Zürich, Penn State) and a PhD in Information Engineering, reflecting a rare mix of computational rigor and practical systems engineering. Colleagues value his ability to translate advanced optimization techniques into governance-relevant solutions that explicitly account for competing sectoral demands.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Ingegneria dell'Informazione, Doctor of Philosophy (Ph.D.), Ingegneria dell'Informazione at Politecnico di Milano
ingegneria, architettura, design, ingegneria, architettura, design at Alta Scuola Politecnica
Laurea Specialistica in Ingegneria per l'Ambiente e il Territorio, I Facoltà di Ingegneria Ambiente, Costruzioni, Industria, Intersettoriale, Laurea Specialistica in Ingegneria per l'Ambiente e il Territorio, I Facoltà di Ingegneria Ambiente, Costruzioni, Industria, Intersettoriale at Politecnico di Torino
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