معرفی
Professor Alessandro Chiuso is a Full Professor in the Department of Information Engineering at the University of Padova, Italy. His research focuses on control systems, machine learning, system identification, and their applications to neuroscience and medical imaging. He has contributed to advancing data-driven control methodologies, regularization techniques, and brain network modeling.
His work bridges theoretical control systems with practical applications, including predictive control under uncertainty, nonlinear system identification, and understanding brain dynamics through fMRI and PET data. Notable areas include developing algorithms for adaptive control, optimizing brain region interactions, and analyzing metabolic-functional couplings in neurological conditions.
Recent publications highlight advancements in policy gradient methods for LQR control, sparse dynamic causal models for brain aging studies, and predictive control frameworks for stochastic systems. His research emphasizes the integration of machine learning with classical control theory to solve complex real-world problems.
