Principal Investigator: Ricard Solé Principal Investigator: Ricard Solé


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The ICREA-Complex Systems Lab, led by Ricard Solé, is formed by an interdisciplinary team that explores the evolution of complex systems, both natural and artificial, in search of their common laws of organization. We do both theoretical and experimental work, working in close collaboration with the Santa Fe Institute. We study the origins and evolution of complex systems and the boundaries of such complexity (and how to break them) using methods from statistical physics, synthetic/systems biology and network theory.

Bioengineering the biosphere: We explore (mathematically and experimentally) the potential scenarios that could allow us to redesign our biosphere using synthetic biology as a major engineering approach.

Major synthetic transitions: Synthetic biology, evolutionary robotics and artificial life allow us to re-create major innovations of biological evolution while searching for new ones. We want to make a new synthesis of major transitions in human-made, simulated, natural and synthetic systems and look for novel types of artificial transitions. 

Unstable evolutionary dynamics: Both cancer populations and RNA viruses display high levels of genetic instability. We study how this unstable state contributes to adaptation and, perhaps, to new forms of therapy based on the presence of lethal thresholds. 

Technological evolution: Both technology and biology share a number of relevant traits. Our lab explores the similarities and differences between them, with special attention to the origins of innovation and the physics of the underlying landscapes.

Cognitive networks: We study the architecture and evolution of language and brain networks. Our goal is to develop theoretical models of language emergence and change and explain the origins of their complexity.

Theoretical network evolution: We are developing theoretical models of network evolution, with a special interest in the open-ended nature of complexity, its hierarchical organization and the presence of catastrophes and breakpoints in large-scale dynamics

Synthetic biology and artificial life: We use approaches from artificial life and synthetic biology to explore questions related to information, multicellularity, collective intelligence and ecology as well as biomedical applications.

Biological computation: We explore how to create new forms of multicellular computation and how to build a complex biological computer. By evolving bio-inspired hardware and software, we also search for robust solutions to complex problems


Lab website: Complex Systems Lab

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