From cities and economies to brains and ecosystems, many complex systems share striking regularities: similar patterns repeat across scales, and sudden transitions can emerge from seemingly stable dynamics. This workshop brings together leading researchers to explore how ideas such as scaling laws, criticality, and self-organization help us understand collective behavior in systems composed of many interacting parts. By crossing traditional boundaries between physics, biology, economics, and urban science, the meeting aims to uncover unifying principles that govern complexity in the natural and social world.

A central theme of the workshop is the tension between robustness and fragility in complex systems: how large-scale regularities coexist with fluctuations, instabilities, and critical transitions. Concepts such as allometric scaling, universality, and self-organized criticality offer powerful lenses to connect phenomena as diverse as metabolic rates, neural activity, epidemic spreading, financial markets, and urban growth. The invited speakers have played a key role in shaping these frameworks, both theoretically and through data-driven approaches.

Understanding scaling and criticality has become particularly urgent in the context of rapid urbanization, climate change, global pandemics, and increasing socio-economic interconnectedness. Cities are growing faster than ever, financial and ecological systems are tightly coupled, and societies are repeatedly confronted with cascading failures and abrupt transitions. At the same time, unprecedented volumes of data now allow for systematic empirical tests of theories that were once purely conceptual. This workshop leverages these developments to ask whether general principles of complex systems can inform prediction, resilience, and policy, making it especially timely for researchers working at the interface of theory, data, and real-world applications.

Programme

About the speakers

Prof. Geoffrey West is a theoretical physicist and one of the founders of modern complex-systems science. As former President and Distinguished Professor at the Santa Fe Institute, he played a central role in establishing interdisciplinary approaches to complexity across the natural and social sciences. His work on allometric scaling in biology revealed remarkably simple power-law relations governing metabolism, lifespan, and growth across species. More recently, he has been a driving force behind the quantitative science of cities, uncovering systematic scaling laws that relate urban indicators—such as innovation, infrastructure, and energy use—to city size. His research combines theory, data, and universality arguments, and has had wide impact across physics, biology, urban studies, and public policy.

Prof. Miguel A Muñoz is a statistical physicist at the Universidad de Granada and a leading authority on critical phenomena in non-equilibrium systems. He is particularly well known for his contributions to the theory of self-organized criticality, absorbing-state phase transitions, and dynamical scaling. His work has been influential in applying ideas from statistical physics to living systems, including neuroscience, population dynamics, and theoretical ecology, where criticality has been proposed as a functional operating point. Muñoz’s research is characterized by a deep interplay between analytical theory, numerical simulations, and conceptual clarity regarding universality and robustness in complex adaptive systems.

Prof. Marc Barthelemy is a statistical physicist at the Institut de Physique Théorique and a prominent figure in the study of complex networks and urban systems. His work spans topics such as network structure and dynamics, spatial networks, epidemic spreading, and mobility patterns. In the context of cities, he has developed quantitative frameworks to understand urban morphology, transportation networks, and congestion, critically examining the limits and interpretation of scaling laws. Barthelemy is known for combining rigorous physical modeling with empirical analysis, offering a nuanced perspective on how spatial constraints and heterogeneity shape large-scale collective behavior.

Prof. Tiziana Di Matteo is Professor of Econophysics in the Department of Mathematics at King’s College London. Her research lies at the intersection of statistical physics, complex systems, and economics, with a focus on financial markets, macroeconomic dynamics, and social systems. She has made significant contributions to understanding correlations, scaling, and network structures in financial time series, as well as the dynamics of economic crises. By importing tools from physics into economics, her work sheds light on systemic risk, market instability, and the emergence of collective behavior in socio-economic systems