SciCom

Scientific Computing Group

Given the complexity of current problems, the experimental and theoretical approaches need a computational counterpart. It is in this context where the work of our group focuses: the development and application of mathematical and computational models to the study of real problems of scientific or engineering interest.

Our group tackles this task by building physical-mathematical models translated into efficient software tools.

Our current interest focuses on the treatment of systems of interrelated elements. Despite its novelty, this approach — complex networks — has proven incredibly useful for analyzing, interpreting and predicting the behavior of complex systems. Typical examples are: the economic system, social networks, the Internet, the www, the metabolic system, the genome or the set of human diseases with a genetic basis.

The studies carried out in this area show the existence of a common behavior in networked systems, regardless of their physical nature — economic, social, biological or technological —.  In this broad field, we focus on the development and application of models and computational techniques for the identification, description and control of the internal structure of complex networks. The key point in this context is the identification of groups of related entities — communities — in the network.

SciCom Members
Dr. Camelia Muñoz Caro
Dr. Alfonso Niño Ramos
Dr. Sebastián Reyes Ávila 

Research lines

Research lines:

The research lines we consider are:

Methodological

Generation of test models, benchmarks, and validation of community detection methods

Development of community detection methods for treatment of large data volume problems (big data) on distributed computing environments. 

Applied

Cybersecurity

Evolution of communities in social networks.

Identification of bioactive compounds with similar biological activity and prediction of side effects.

In particular, the applied component offers an extraordinary way of collaboration with teams from other disciplines.


Contact information

Dr. Alfonso Niño Ramos
Alfonso.nino@uclm.es

Tel.: (+34) 926 295 300 ext.  6474 / 3720
Fax: (+34) 926 295 354


Website

http://scicom.esi.uclm.es/