Complexity science, applied

I am a computer scientist first, trained in multi-agent systems and a builder by instinct, and what unifies my work is a method rather than a territory: the computational study of complex adaptive systems. That method is deliberately indifferent to domain. One repertoire (agent-based, system-dynamics, and discrete-event simulation, now coupled with generative AI) lets me ask a single question in many settings: how do adaptive agents, whether people, institutions, economies, or AI systems themselves, coordinate, anticipate, and govern their own behaviour under uncertainty? Pursuing it has taken me across suicide-prevention and health-system policy, the macroeconomics and labour dynamics of generative AI, the energy systems AI runs on, and, most recently, the internal architecture of agency and governance within AI agents and their collectives. I resist a single label because the problems that interest me live between fields, in the translation space where computational precision meets consequential decisions, and complex-systems thinking is how a computer scientist earns the right to work there.

Visualisations and interactivities

Interactive models and explorable diagrams that accompany the research. They are built to be played with, not just read.