data-driven-science

SCHeMa (Scheduler for scientific Containers on clusters of Heterogeneous Machines) is an open source platform to facilitate the execution and reproducibility of computational experiments on heterogeneous clusters.

Data-driven framework for Dynamic Mode Decomposition (DMD) and Koopman-based analysis of dynamical systems, with applications to noisy and low-resolution data.

Code for my BSc thesis about SINDy at Bocconi University

ConAx is a communicative platform to stack and share multi-modal research data. It’s a service for transformation and structural reconciliation of open research frameworks to create R&D and R&I projects.

Comparative cosmology framework showing how CPT-Siamese phase dynamics resolves the main failures of ΛCDM: H₀ tension, σ₈ tension, Axis of Evil, JWST early galaxies and vacuum energy. Includes analytic model, toy simulations, and H(z), q(z) figures. Open reproducible science.

Data-driven identification and NMPC of a Quadruple Tank System using Bilinear Koopman Realizations and Physics-Informed Neural Networks (CoDIT 2026).