Matteo Marsili

Matteo Marsili is a Senior Research Scientist at the Quantitative Life Sciences Section of the Abdus Salam International Centre for Theoretical Physics (ICTP) in Trieste, Italy. He holds a PhD from SISSA, Trieste (1994) and has held postdoctoral positions at Manchester University, Fribourg University (Switzerland), and SISSA. He joined ICTP in 2002, initially in the Condensed Matter and Statistical Physics (CMSP) Section before transitioning to the Quantitative Life Sciences Section.

His research spans interdisciplinary domains, applying statistical physics to complex systems. Key areas include non-equilibrium statistical mechanics, critical phenomena, quantitative finance, statistical inference, machine learning, systems biology, and neuroscience. He investigates how collective behaviors emerge from interactions among simple units—such as particles, neurons, or financial traders—using tools from probability, information theory, and thermodynamics.

His recent publications (2020–2025) show a strong focus on information-theoretic approaches to learning, relevance quantification, deep learning, and optimal inference. Themes include Bayesian modeling, minimal complexity, self-organized criticality in neural networks, and thermodynamics of information in financial markets. His work frequently appears in journals like Physical Review E, Journal of Statistical Mechanics, Physics Reports, and PLoS ONE.

Matteo Marsili has collaborated extensively with researchers such as Y. Roudi, R.J. Cubero, J. Song, and R. Xie, suggesting active mentorship and team leadership. While no formal awards are listed, his sustained publication record in high-impact journals reflects significant scientific contributions. His lectures at institutions like the Kavli Institute and IHÉS further highlight his academic influence.