Adriano Gualandi

My research focuses on the study of nonlinear dynamical systems in geophysics, extreme events and their related hazard. I study time series of various observables, including seismological, geodetic, and meteorological data. My main focus is on Solid Earth physics, with particular interest in seismology and geodesy. I use data analysis techniques ranging from classical statistical approaches to more modern machine learning tools to extract the relevant tectonic information out of the available observations. Once that this information is available, kinematic and dynamic models can be realized to explain the observations. I use both physics-driven and fully data-driven approaches to characterize the dynamics of the systems at hand. I am particularly interested in slow and regular earthquakes, but I work also on the interaction between Solid and Fluid Earth, as well as the interaction between volcanic and tectonic processes. Causal links in complex and highly nonlinear systems are not always obvious, and I am interested in both real-world applications and methodological advancements aimed at unveiling these hidden connections. Given the limited information available when studying geophysical problems, a probabilistic description of the world is often necessary. For this reason, I use both deterministic and stochastic models in my work.