Luca Riccardi
PhD thesis title: Computational Methods for Enhanced Decision-Making in Complex Industrial Systems
Academic Tutor: Enrico Zio
Academic Supervisor: Enrico Zio
Industrial supervisor: Michele Compare
Affiliate external company or research group: 3rdPlace s.r.l.
PhD cycle: 40° (see all student profiles of the same cycle > LINK)
BSc: Mathematical Engineering, Politecnico di Milano
MSc: Mathematical Engineering - Statistical Learning, Politecnico di Milano
Thesis abstract
My PhD research focuses on building explainable and robust Grey models, which merge the soundness and interpretability of physical models (White models) with AI’s data-driven insights (Black models) to transcend the inherent limitations of each standalone model.
Personal interest in my research theme
In critical infrastructure, predictive models and digital twins are only as valuable as they are trustworthy. Because black-box AI lacks transparency, industry operators are often hesitant to rely on it for high-stakes decisions. I specialize in grey-box modeling, fusing physical laws with data science to create AI-driven decision tools that are accurate, interpretable, and practical for real-world operations.
