Alexandros Alexakis

Alexandros Alexakis is a Senior Associate at the Institute for Advanced Dynamic Uncertainty, where his work focuses on probability theory and its role in the rigorous construction and analysis of stochastic models for large and complex systems. He holds a PhD in Mathematics from the National and Kapodistrian University of Athens (Department of Mathematics), where his doctoral research developed limit theorems for weakly dependent random sequences under generalised Lindeberg-type conditions, and derived rates of convergence in the central limit theorem for classes of functionals arising in the stochastic modeling of spatially interacting populations.

Following his doctorate, Alexakis extended his work to random field models — probability structures indexed by spatial or temporal parameters — and investigated their ergodic and mixing properties under non-stationary perturbations. This line of research produced criteria for the validity of spatial laws of large numbers and functional central limit theorems in settings relevant to agent-based and heterogeneous-population models, where classical independence assumptions fail and the geometry of interaction determines the asymptotic behaviour.

At IADU, he applies probabilistic limit theory to questions arising in the Institute's work on distributional dynamics: bounding the rate at which empirical distributions of large agent populations converge to their mean field limits, establishing concentration inequalities for policy-relevant statistics, and providing rigorous probabilistic foundations for the approximation arguments that underlie numerical methods in high-dimensional stochastic systems.