Decoding Complexity in Ecology and Economics: Statistical Physics & Data -Driven approaches
Cagliari (Italy) 9-11 July 2025
In recent years, there has been rapid progress in identifying common traits that govern the functioning of complex ecosystems and the dynamics of markets with multiple interacting agents. From competition for limited resources to the tradeoff between evolution and adaptation, as well as the ubiquity of non-linear and feedback mechanisms, general and unified frameworks can be identified that govern both how species behave in complex ecosystems and trading agents perform operations in financial markets.
This satellite conference will explore how statistical physics may reveal the fundamental principles underlying complex systems, from terrestrial environments and microbial communities to social and economic networks. By employing advanced modeling tools such as network theory, statistical inference, and random matrix theory, we aim to investigate the complex dynamics of such interdisciplinary systems and the universal mechanisms that drive them. Recent advancements in artificial intelligence tools (e.g., natural language processing techniques and Large Language Models) and data-driven approaches provide novel insights and frameworks – particularly in the analysis of large-scale unstructured data – for the identification of hidden patterns within ecological and economic communities.
The meeting will foster methodological cross-fertilization between the fields of economy and ecology, providing a venue for the exchange of information about the latest developments in the field. We are aiming towards an inclusive and gender-balanced event, with particular attention paid to early-career researchers and colleagues from under-represented groups.
Key topics will include:
- Emergent phenomena in ecology and economics
- Network dynamics in biological and financial systems
- Phase transitions, critical phenomena, and scaling laws
- Systemic resilience, robustness and stability
- Stochastic processes and noise effects in population dynamics and market behavior
- Agent-based models of interactions in ecological and economic systems
- Data-driven models of ecosystems and markets
- Natural Language Processing for Economics and Social Sciences
- AI-Driven Predictive Models for Economic and Biological data
Organizing Committee
- Ada Altieri (Université Paris Cité, Paris, France)
- Silvia Bartolucci (University College London, London, UK)
- Pierpaolo Vivo (King’s College London, London, UK)
- Marco Ortu (Cagliari University, Italy)
- Giulia Contu (Cagliari University, Italy)
Contact us: eco2statworkshop[at]gmail[dot]com
