Mission Statement
We seek to understand how interaction-driven evolutionary, ecological and informational processes generate complexity across scales, using theoretical insight to reveal general principles and responsibly inform real-world challenges.
Five Commitments
More expansively, the group's mission rests on five intertwined commitments.
Process over system
The unifying object of study is not a particular organism or ecosystem, but interaction-driven dynamics. Whether the context is microbial communities, plant pathogens, gene drives, animal behaviour, or collective human narratives, the central question remains: What rules of interaction give rise to structure, cooperation, conflict, resilience, or collapse?
Eco-evolutionary-learning dynamics
The work consistently rejects the separation of ecology, evolution and learning. Instead, it treats them as coupled feedback systems unfolding on overlapping timescales. The mission is to understand these feedback loops mechanistically and mathematically — especially where they generate non-intuitive or emergent outcomes.
Theory as a generative engine
The ethos "insight preceding application" is not rhetorical — it reflects a methodological stance. The group views theoretical biology not merely as a descriptive tool but as a generative framework capable of revealing new phenomena, predicting counterintuitive dynamics, and reframing applied problems before intervention. Application is important, but it is downstream of conceptual clarity.
Cross-scale curiosity
A persistent theme is movement across levels of organisation — genes, cells, individuals, populations, communities, and even societies. The mission implicitly embraces the idea that similar dynamical principles may operate across scales. This reflects a deep curiosity about emergence: how higher-order structure arises from lower-level interactions.
Responsible translation
Although curiosity-driven at its core, the research does not remain abstract. It deliberately connects to antimicrobial resistance, agriculture, sustainability, infectious disease control, and cultural systems. The implicit mission is not only to understand complexity but to inform decisions in systems where evolution cannot be ignored.
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