Models and algorithms for accessing information in Internet

A large amount of data can be represented as large graphs or digraphs, where the vertices represent the data and the edges some type or relation (proximity, dependency, correlation). One of the big issues in data science is the problem of reporting, i.e., inferring information from the massive data and formulating predictions. We want to study the propagation and the access to information in the Internet. We aim at studying information propagation in the net using computational game theory, modelling this propagation in terms of influence spread. We are also interested in the study of information access using the paradigm of graph databases, i.e. considering the internet as a huge graph database.

Models and algorithms for process mining

. mining software can help organizations to capture information from enterprise transaction systems and provide detailed information about how key are performing. We are interested in the study of the mining of processes using heterogeneous sources, including not only system logs, also documents, or audio and image files describing informally some given processes. We aim to develop new process models based on simple components the development of algorithms for obtaining adequate samples from data streams that could be used for the analysis of logs.

. models help reasoning about the behavior of big networks of systems and could yield more efficient algorithm designs. are referring to the kind of systems such as the internet of things. A system can be modelled as an attribute graph and the computational evolution of network of systems as a sequence of graph transformations. We are interested in the definition of a logic that allows us to reason about properties of the graphs. Our objective is the definition of a set of tools to verify the correctness of the algorithms defined on our model.

The problems described as cooperative games are essentially motivated by everyday situations related to political science, sports, economics, social sciences and certain aspects of technology. We are interested in the study of problems linked to voting games and social choice, among others. We want to go deeper in the mathematical structure of different classes of voting systems and to perform a critical and algebraic analysis of certain notions of power and stability in situations of cooperation. We are also interested in the definition of new coalitional values, as well as bisemivalues, designed to take into account players' attitudes with regard to cooperation, their axiomatization and computation.

In this area we face various challenges in the design automation of nanoelectronic integrated circuits that require efficient algorithmic solutions. The effort is focused on three topics: synthesis of layout for memory-dominated systems, architectural exploration of elastic systems and synthesis of asynchronous circuits. The first two topics are strongly related to the physical design (placement and routing) of large electronic systems. The third topic implies a consolidation of the research carried out for the logic synthesis of clockless control systems. A common aspect of all the aforementioned problems is the treatment of spaces of solutions that have a combinatorial explosion. We will often resort to techniques related to constraint programming using satisfiability and linear programming solvers. Metaheuristics for efficiently navigating along the solution space will also be used when required by the size of the solution space

We are interested in developping new multidimensional data structures, which have applications in fields as geographical information systems, proximity search, computer graphics, and many other. In particular, the study of the multidimensional data structures used in associative searchers, like the partial match, orthogonal range or nearest neighbor queries, present in applications like GoogleMaps, TripAdvisor, Booking, etc…

We are referring basically to graphs like complex networks or large ad-hoc communication or biological networks. We work on stochastic and game theory models for spread of disseminations on those kinds of graphs, for instance to model the behavior of spread of infections and healing, on some specific networks as well as design efficient algorithms and heuristics for particular problems. We analyze problems on static and dynamic networks from the perspective of game theory. We focus on three directions. Non-cooperative models for network formation, in particular the analysis of properties of the equilibria networks and of the dynamics creating such networks. Network processes, as source for models of cooperation and decision making. Those scenarios will be analyzed as cooperative combinatorial optimization games as well as evolutionary non-cooperative games. We also plan to develop efficient algorithms for graph classes used in Bioinformatics, in particular trees and phylogenetic networks.