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Evolution & Optimization

Optimization principles are a useful reference to understand biological systems. But evolution does not produce in general perfectly optimal systems so we must expect significant deviations from optimality. As part of my PhD thesis at de Polavieja lab, we developed a way to perform testable predictions about these deviations. Assuming that suboptimal states can exist, but that the probability of a given state is higher for higher values of the objective function, we predict a correlation between the impact of each component of the system on the objective function and its deviation from the optimum.

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Collective behavior & decision-making

As part of my PhD thesis at de Polavieja lab, we have developed a model of collective decision making, based on Bayesian estimation of the environment using both social and non-social (sensory) information. We obtain a simple analytic model that reproduces with great accuracy datasets of different species (zebrafish, sticklebacks and Argentine ants).

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Tracking systems

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