Dynamical Processes in Complex Network based on Machine Learning
Characterizing time-varying networks: methods and applications
Designing cell signaling pathway dynamic models through the combination of differe...
Grant number: | 23/09522-1 |
Support Opportunities: | Scholarships abroad - Research Internship - Master's degree |
Start date: | September 25, 2023 |
End date: | March 24, 2024 |
Field of knowledge: | Physical Sciences and Mathematics - Mathematics - Applied Mathematics |
Principal Investigator: | Francisco Aparecido Rodrigues |
Grantee: | Ricardo Tetti Camacho |
Supervisor: | Jurgen Herbert Gustav Kurths |
Host Institution: | Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
Institution abroad: | Potsdam Institute for Climate Impact Research, Germany |
Associated to the scholarship: | 22/02013-1 - Dynamical processes in mobile agent networks, BP.MS |
Abstract Mathematical modeling is essential for understanding spreading processes in complex networks. While much research has focused on static networks, the importance of temporal networks is becoming increasingly recognized. In this project, we aim to develop a novel approach to modeling temporal networks using mobile agents and a movement structure that allows for the creation of dynamic clusters. Our primary research questions include: How do dynamic processes in temporal networks affect the spread of information or disease? How do these processes interact with multilayer networks, and what are the implications for real-world phenomena? By addressing these questions, we hope to advance our understanding of complex systems and provide insights for optimizing interventions in various domains, such as public health and social media. (AU) | |
News published in Agência FAPESP Newsletter about the scholarship: | |
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