Biological computation

We are exploring 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.
See our paper on Distributed biological computation.

Synthetic biology and Artificial Life

We use artificial life and synthetic biology approaches to explore questions related to information, multicellularity, collective intelligence and ecology as well as biomedical applications.
See our paper on The space of biocomputation.

Theoretical network evolution

We are developing theoretical models of network evolution, with special interest in the open-ended nature of complexity, its hierarchical organization and the presence of catastrophes and breakpoints in large-scale dynamics.
See our paper on Origins of hierarchy in networks, PNAS.

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.
See our paper on Language networks.

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.
See our paper on Technological innovation.

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.

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