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AlgoLab is a research group focused on designing, studying, analyzing and implementing efficient algorithms, mainly combinatorial algorithms, for computational problems. The group is associated with the CS Dept. of Univ. Milano-Bicocca, but includes members of neighboring universities and research groups.

While the focus is on Computer Science, we are an interdisciplinary group, without defined boundaries on the fields of application of the algorithms studied. We are especially interested into algorithms and data structure to manage massive datasets (Big Data), as trivial or brute-force algorithms can suffice on modest dataset. On the other hand Big Data require linear or sublinear time algorithms with very small space requirements — such as streaming algorithms and succint data structures — or parallel algorithm.

Some more specialized topics of interests are:

  • Text algorithms and data structures. We study algorithms and data structures for indexing and querying huge text collections.
  • Combinatorics on words. We study different notions of distance between words, with a focus on classical definitions such as the longest common subsequence and the shortest common supersequence.
  • Algorithms on trees. We study combinatorial algorithms for tree comparison and phylogeny reconstruction from matrices that encode the set of characters that the leaves have (e.g. the perfect phylogeny problem).
  • Graph algorithms. We study some notions of graph decompositions — such as modular decomposition — and graph-based clustering (consensus and correlation clustering).
  • Connections between texts and graphs. Modeling text problems, such as the shortest superstring problem, as  graph problem is a powerful tool to develop new algorithms. All known genome assembler (a genome is essentially a very long string which must be reconstructed from a set of substrings) are built upon the notion of string graph or de Bruijn graph.
  • Computational, approximation and fixed-parameter complexity. We study how different parameters determine whether a certain problem admits and efficient solution, while classical computational complexity focuses on a single parameter: the size of the instance.

We strive for a delicate balance between theoretical and experimental aspects, as we believe it is the only way that a research activity that can produce results useful outside academia. In fact, there are several algorithms that are efficient from a theoretical viewpoint (that is, polynomial time algorithm) but they do not have an efficient implementation, either because the algorithm engineering that is necessary to this purpose has not been done, or is impossible to do. On the other hand, there are some cases where exponential or super-polynomial time complexity result in implementations that are efficient in practice (such as the simplex algorithm).

Often efficient implementations stems form combinatorial properties of the instances that we want to solve, and it is hard to find a priori which properties can lead to fast implementations. An example is the Burrows-Wheeler Transform that is based on sorting all rotations of the text, has been introduced to compress texts but, a decade later, has shifted its main application in text indexing.

Recent Posts

Algolab at Recomb 2018

RECOMB 2018 is the 22nd edition of a series of well-established scientific conferences bridging the areas of computational, mathematical, statistical and biological sciences.  The 2018 edition was held in  Paris from April, 21st through 24th of 2018, and was preceded by a series of satellite workshops on the 19th-20th of April. Luca Denti and Murray … Continue reading Algolab at Recomb 2018

Advanced Techniques for Combinatorial Algorithms (2018)

This is the first PhD-level course on the design and the analysis of efficient algorithms, with a strong emphasis on theoretical aspects. The prerequisites are a very basic knowledge of graph theory and computational complexity, as well as a good understanding of undergraduate-level courses of algorithms, discrete mathematics, and operation research. It is not necessary … Continue reading Advanced Techniques for Combinatorial Algorithms (2018)

Workshop on Combinatorial Algorithms in Bioinformatics

January 26th, 2018 Univ. Milano-Bicocca. Building U14 – Room Aula Seminari Theme and scope The ever increasing amount of biological data available requires more efficient tools for managing and analyzing those data. While a widely used line of attack is to throw huge computational resources at the problem and using known methods as black boxes … Continue reading Workshop on Combinatorial Algorithms in Bioinformatics

AlgoDay 2017

When 26 July 2017 Where Sala Seminari, U14, DISCo, Univ. Milano-Bicocca Why We are witnessing an explosion in the availability of data, ranging from social media interactions, to biological sequences, to sensor data, which share the huge availability and low cost. Since those data are, by far, impractical or impossible to keep in memory, we … Continue reading AlgoDay 2017

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