JOSE CASADIEGO

© Jose Casadiego 2015

## Network dynamics as an

## inverse problem

The dynamics of networks dominate the
world around - and in - us. Power grids,
transportation systems, neural circuits
and gene regulatory networks are just
some of the many examples of such
networks in action. To understand
mechanisms underlying collective
network dynamics, typically a forward
perspective is taken and mathematical
models of given systems are explored as a
function of their parameters. I am
developing theory for analyzing networks
from an inverse perspective with
emphasis on network design and
adaptability.

## Revealing networks from

## dynamics

Inferring network connections is problem
arising in a broad variety of multidisciplinary
fields. Nevertheless, state of the art
approaches are still far from solving the
entire problem. Many efforts have been
made to tackle it but current methods (i) are
susceptible to recover spurious connections,
(ii) are constrained to only specific cases or
(iii) require an extensive sampling of network
dynamics. By exploiting concepts of
nonlinear dynamics, I am currently
developing theory on complex networks for
retrieving network connectivity from available
data while overcoming aforementioned
limitations.

## Physics of complex

## networks

Network approaches have been vastly
used to describe the onset of non-trivial
collective behavior arising in many areas.
Generally, these systems are mostly
analyzed with respect to their topology
(e.g. regular, small-worls, random).
However, recent results strongly suggest
that networks may be more than their
structure. By adopting a novel
representation of network dynamics, I am
pursuing to extend known results of
classical mechanics to complex networks.
Research