Dr. Nicolas Payette

Research Software Engineer

Nicolas has been obsessed with programming since getting his first computer as a child (back when computers were not ubiquitous) and learning BASIC. He started his career as a professional software developer before gradually getting absorbed into academia and eventually completing a PhD in Philosophy at UQAM (Université du Québec à Montréal).

The defining trend of his academic career has been a focus on agent-based models, or ABMs: computer simulations that represent complex systems as collections of autonomous agents interacting with each other and with their environments. He has collaborated on models where these agents were (amongst other things) scientists, mafiosi, chimps, terrorists, and elephants, spanning a wide range of topics across the social sciences.

Many of these models were written using NetLogo, a specialised ABM platform that is used extensively in both education and research. Nicolas was once part of the core NetLogo development team and has written many extensions for it. NetLogo is written in Scala, a hybrid object-functional programming language for which he has a special fondness.

In more recent years, his attention has been captured by another agent type: fishers. He is the lead developer of POSEIDON, a generic ABM of fisheries that has been applied to cases ranging from small fishing communities in Indonesia to large-scale tropical tuna fishing in the Eastern Pacific Ocean. Nicolas is currently working on the SURIMI project, aiming to integrate POSEIDON and models like Ecopath with Ecosim (EwE) into the European Digital Twin of the Ocean. POSEIDON is written in Java and based on the MASON platform, with extensive use of R for results analysis.

Nicolas loves to teach about all these topics and has been on the faculty of the yearly Behave Summer School on ABM since 2016. He also teaches on the OxRSE Software Engineering course and regularly gives invited lectures on R and reproducible research to anthropology students as part of their Quantitative Methods course.