Stefano Riva

Stefano Riva

Research Scientist specializing in Physics-Informed AI/ML for engineering and design. Proven track record in reduced-order models and data-driven state estimation, bridging traditional numerical solvers with machine learning to accelerate high-fidelity simulations.

Constrained Sensing and Reliable State Estimation with Shallow Recurrent Decoders on a TRIGA Mark II Reactor

Published in Chemical Engineering Science, 2026

Paper URL

Authors: Stefano Riva, C. Introini, J. Nathan Kutz, A. Cammi

Abstract: Shallow Recurrent Decoder networks provide accurate state estimation in engineering systems such as nuclear reactors. This work presents the first application of SHRED to a deployed reactor concept (TRIGA Mark II), integrating hybrid synthetic and experimental temperature data and assessing robustness under physically constrained sensor locations and model-to-data discrepancies.