Exploring complexity through networks, computation, and data.
We build and analyse complex networks across social, urban, and informational systems to understand how their structure shapes dynamics, robustness, and emergent behaviour at multiple scales.
We develop agent-based, optimisation, and biologically inspired computational models to simulate and predict complex system dynamics — from crime patterns and misinformation spread to urban inequality and human mobility.
We apply machine learning, statistical inference, and AI-driven analysis to large-scale datasets, uncovering hidden patterns and emergent properties that support evidence-based understanding of complex social and urban systems.
Placeholder description of this research question. Replace with the lab's actual focus area, specific organisms or systems studied, and key methods.
Placeholder description of this research question. Replace with the lab's actual focus area, specific organisms or systems studied, and key methods.