Contact: Paula Murmann
Take a simple undirected graph where nodes represent individuals and edges represent the contacts between them. On this graph we consider a SI (susceptible-infected) epidemic process. I.e., each node can be in a susceptible or infected state and nodes transition from the susceptible into the infected state if they get infected by a neighbour.
The goal of this project is to create a simulator of this process depending on the underlying structure and compare the infection model to more realistic real-world simulators (e.g. https://www.nature.com/articles/s41591-020-1036-8.pdf).
Implement a simulator for the spreading process on a synthetic graph model
Test implementation on real world graph
Adapt published Covid simulator to problem parameters
Compare published simulator to theoretical simulator
Familiarity with random graph models, probability, sampling techniques
Strong programming skills & good code organisation/documentation/maintainability
Language: python or take this project as a chance to learn a new language
For published simulators, you will need to familiarise yourself with R