Talk - Stochastic Models of Higher-Order Networks -- Point Processes and Topological Data Analysis

Abstract

During his PhD studies, Péter Juhász researched stochastic network models that describe how complex systems emerge from random interactions. Such models are used to capture the structure of communication systems, biological networks, and collaborations, where randomness and group interactions play a key role. Péter Juhász focused on how fundamental network characteristics, such as node degrees and connection patterns, scale in large systems and how interacting groups of nodes beyond simple pairs shape the overall network. The research provides new mathematical insights into how novel stochastic network models influence both local and global structures of complex systems, advancing their understanding.

Péter Juhász

Quantitative Researcher