International Conference on Hyperuniformity and Topological Data Analysis

Description

The conference on “Hyperuniformity and Topological Data Analysis (HTDA)” brings together researchers exploring the intersection of geometric structure, statistical physics, and modern data-analytic techniques to better understand complex systems. Hyperuniformity, central to my PhD research, describes a class of structures that exhibit suppressed density fluctuations, occupying a regime between complete disorder and perfect crystalline order. My doctoral work has focused on analysing two-dimensional, geometry-driven hyperuniform systems generated through Voronoi-based iteration and relaxation algorithms, which are widely used for space partitioning and data clustering into uniformly shaped convex cells. In parallel, I have actively applied tools from TDA to extract and quantify structural features of such kind of evolving systems, enabling deeper insight into how local interactions give rise to emergent global properties. I have been invited to contribute as a speaker at this conference, where I will present findings from my PhD alongside recent work extending TDA methodologies to study information flow mediated by AI systems.

Period	6 Jul 2026 → …
Event title	Speaker at the International Conference on Hyperuniformity and Topological Data Analysis
Event type	Other