I’m am computational social scientist and data scientist with a background in political communication and social media research that specialises in agent-based simulation, social network analysis and the computational study of social media behaviour.
For the last three years, I was a Research Associate in Computational Social Science at Durham University designing and evaluating algorithms for realistic artificial social networks in Julia by creating a taxonomy of existing generator papers, accessible as an interactive, open-access database (RShiny dashboard), in addition to exploring the interdependencies of social network’s structural properties.
For my PhD in Politics at Glasgow University (2023) I designed and implemented an agent-based model of online polarisation and offline protest mobilisation, applied to Catalonia’s independence movement in Spain.

Peter Gerbrands is a Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure FIRMBACKBONE. He teaches data science courses and econometrics as well as supervising bachelor, master, and Ph.D. theses. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In the Fall of 2023, he was a Visiting Research Scholar at SUNY Binghamton in NY.