Marcos’ research explores the intersection of computational social science, behavioural data science, and complex systems. He uses behavioural data and computational modelling to develop theory-grounded models that help us understand real-world social phenomena—ranging from face-to-face interactions to online browsing behaviour to urban crime. He draws on tools and concepts from criminology, sociology, network science, information theory, machine learning, and mathematical and agent-based modelling.