These are the topics which hold more intense research activity in the Department:

Algorithms and Combinatorial Optimization
Activity: research in a broad spectrum of combinatorial optimization problems and its applications, with particular focus on complexity issues, design and analysis of efficient exact and approximation algorithms, use of polyhedral approaches, and other techniques. Research topics include semidefinite optimization, probabilistic methods, network design, routing, packing, as well as game theoretical problems.

Bioinformatics

Activity: to study the application of mathematical and computing techniques for the generation and management of information in the Biology and Biotechnology areas.

Combinatorics and Graph Theory
Activity: research in discrete and computational geometry, matroid theory, probabilistic methods and random combinatorial structures, graphs and hypergraphs (structural properties, extremal problems, coloring, decomposition, and others).

Computer Music
Activity: to develop research related to the following issues: the processing of sound signals, acoustic simulation in music environments and listening rooms, automatic analysis of musical signals, sound synthesis and interactive performance in the context of electroacoustic music.

Cryptography and Data Security
Activity: to develop efficient (and demonstrably secure) algorithms and protocols based on issues such as integer factorization, discrete logarithm calculation, calculation of bilinear pairing, etc.

Logics, Artificial Intelligence and Formal Methods
Activity: to develop artificial intelligence techniques and study their applications in Computer Science as well as in other areas.

Continuous Optimization
Activity: to research nonlinear programming, convex analysis, operational research and optimization in general, addressing theoretical and algorithmic aspects and applications.

Software Systems
Activity: to develop software systems, especially the distributed ones, the concurrent ones and the ones for storage and retrieval of data; study the evaluation and the definition of technologies that facilitate their construction, maintenance and evolution.

Computer Vision and Computer Learning
Activity: to research the range of methods and techniques through which computer systems may be able to interact with and respond to images and to model learning processes in their many manifestations.

eScience
Activity: to research storage and retrieval of data, image processing, pattern recognition and large-scale computing applied to the design, implementation and management of scientific experiments.