Talk - Stochastic Models of Higher-Order Networks -- Point Processes and Topological Data Analysis
Dec 15, 2025
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0 min read
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.
Date
Dec 15, 2025 2:15 PM — 4:30 PM
Location
Aarhus University
Auditorium D3, 116 Ny Munkegade, Aarhus C, 8000
Authors
Quantitative Researcher
I am a PhD researcher in Mathematics with experience in stochastic modeling, probabilistic analysis, and large-scale simulation, supported by Python/C++ model development.
Previously, I worked as a machine learning researcher at Bosch, where I developed and validated predictive models with a focus on uncertainty estimation and data-driven decision-making.
I am interested in applying quantitative methods to forecasting and risk modeling in energy and financial markets.