BECCUTI Marco

Professore/Professoressa associato/a
Settore scientifico disciplinare: 
INFORMATICA (INF/01)
MarcoBeccuti.jpg
Telefono: 
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Cellulare: 
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Strutture di riferimento

Sede: 
INFORMATICA
Struttura di afferenza: 
Dipartimento di Informatica
Struttura di appartenenza: 
Dipartimento di Informatica

Attività didattica

Attività scientifica

Marco Beccuti  obtained his Ph.D. degree in Computer Science from Università degli Studi di Torino under the joint supervision of the Universitè of Paris Dauphine. His Ph.D. thesis was entitled "Modeling and analysis of probabilistic systems. Formalisms and efficient algorithms" .

From January 2008 to December 2008, a research assistant at "Consorzio Nazionale Interuniversitario per le Telecomunicazioni" (CNIT).

From March 2009 to October 2012 he was a research assistant at the Dipartimento di Informatica of the Università degli Studi di Torino.

From October 2012 to October 2020, he was researcher at the Dipartimento di Informatica of the Università degli Studi di Torino.

He is currently associate professor at Dipartimento di Informatica of the Università degli Studi di Torino, technical coordinator of ELIXIR Node of the Università degli Studi di Torino and scientific coordinator of the laboratory "HPC for biomed and AI" in ICxT . He is also member of "Quantitative Biology" (q-Bio) group, of the "Performance Evaluation and System Validation" group (QMIPS), of "Bioinformatics ITalian Society" (BITS), and of the "Consorzio Nazionale Interuniversitario per le Telecomunicazioni" (CNIT).

His research is currently mainly focused on computational modeling and simulation of complex systems.
In particular he is interested in:

  • Stochastic and hybrid modeling languages;
  • Exact and approximated techniques to analysis the behavior of complex systems;
  • Applications to computational Systems Biology.

Moreover he works on design of bioinformatics algorithms and workflows for the analysis of deep sequencing data (i.e. genomic, transcriptomic and single cell data) with particular emphasis on reproducibility aspects.