09/12/2015

Clara Granell is awarded an international grant to make further research into complex networks

The URV doctoral student has won one of the new competitive grants awarded in 2015 by the James S. McDonnell Foundation for doctoral students who research into complex systems. For two years she will further her understanding of statistics in the United States

This grant is awarded to students who wish to carry out postdoctoral research at the university of their choice anywhere in the world. To this end, the Foundation provides a grant of $200,000. Clara Granell has decided to continue her research at the department of Mathematics of the North Carolina University in Chapel Hill, where she hopes to further her understanding of statistics.

Clara Granell is about to finish her doctorate in Computer Engineering at the URV’s School of Engineering. Her thesis, which she will defend, has been supervised by Àlex Arenas and Sergio Gómez, from the Alephsys Lab research group. Granell studies complex networks, an interdisciplinary field based on knowledge and techniques from applied mathematics, computing, artificial intelligence and statistical physics.

The study of complex systems focuses on systems made up of interacting units that have a collective behaviour and are not just the sum of their individual parts. This interaction creates a network in which the units or nodes have highly heterogeneous connections.

There are many biological, technological and social systems made up of related individual components: for example, computer networks, friendships between people or interaction between proteins. By representing these systems using complex networks makes it possible to apply a wide variety of physical and mathematical tools to understand the structure and the operation of these systems, and, in some cases, even to predict their future operation.

In the next two years at the University of North Carolina, Clara Granell plans to research into network inference. Network inference uses structural information from the network observed and probabilistic models to find a more general model to which the network under study belongs to. This general model is the used to complete the information about the network, possibly for purposes of prediction.

Clara Granell studied Computer Systems at the URV and the UPC-URV-UB interuniversity master’s degree in Artificial Intelligence. If possible, she plans to return to the URV after spending some time in the United States and extending her scientific understanding of her chosen speciality.


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