Saarland University, Machine Learning Group, Fak. MI - Mathematik und Informatik, Campus E1 1, 66123 Saarbrücken, Germany     

Machine Learning Group
Department of Mathematics and Computer Science - Saarland University


Postdoctoral fellow
Faculty of Mathematics and Computer Science,
Saarland University

Saarland University
Saarland Informatics Campus
Building E 1 1, Room 229
66123 Saarbrücken

phone: +49 (0) 681 302 57333



I received my Ph.D. in mathematics from the University of Rome “Tor Vergata”, with the thesis “Advances in Perron-Frobenius theory and algebraic network analysis”. Presently I am a member of the machine learning group at Saarland University. My primary research interests include matrix analysis, computational mathematics, graph theory, and their application to network analysis, machine learning and optimization. My work is mainly aimed at developing and analysing theoretical and computational issues related to spectral properties of graphs and networks, with an emphasis on node centrality and clustering problems. My main present research activity include the anlysis of spectral properties of the p-Laplacian operator and of the modularity matrix on finite graphs, as well related computational issues and applications to the treatment of networks. Surprisingly enough my Erdösh number is 4.

See also my page on Research Gate




  • F. Tudisco and M. Hein
    A nodal domain theorem and a higher-order Cheeger inequality for the graph p-Laplacian
  • D. Fasino and F. Tudisco
    Localization of dominant eigenpairs and planted communities by means of Frobenius inner products


  • P. Mercado, F. Tudisco, M. Hein
    Clustering Signed Networks with the Geometric Mean of Laplacians
    to appear on Proc. Advances in Neural Information Processing Systems (NIPS 2016)
  • Q. Nguyen, F. Tudisco, A. Gautier, M. Hein
    An Efficient Multilinear Optimization Framework for Hypergraph Matching
    to appear on IEEE Transactions on Pattern Analysis and Machine Intelligence (arXiv)
  • D. Fasino and F. Tudisco
    Modularity bounds for clusters located by leading eigenvectors of the normalized modularity matrix
    to appear on Czechoslovak Math.(arXiv)
  • C. Di Fiore, F. Tudisco, P. Zellini
    Lower triangular Toeplitz–Ramanujan systems whose solution yields the Bernoulli numbers
    Linear Algebra Appl. 496(2016), pp. 510-526 (DOI)
  • F. Tudisco
    A note on certain ergodicity coefficients
    Special Matrices 3(2015), pp. 175-185 (DOI)
  • D. Fasino and F. Tudisco
    Generalized modularity matrices
    Linear Algebra Appl. 502(2016), pp. 327-345 (DOI) (arXiv)
  • S. Cipolla, C. Di Fiore, F. Tudisco, P. Zellini
    Adaptive matrix algebras in unconstrained minimization
    Linear Algebra Appl. 471(2015), pp. 544-568 (DOI)
  • F. Tudisco, V. Cardinali and C. Di Fiore
    On complex power nonnegative matrices
    Linear Algebra Appl. 471(2015), pp. 449-468 (DOI) (arXiv)
  • D. Fasino and F. Tudisco
    An algebraic analysis of the graph modularity
    SIAM. J. Matrix Anal. & Appl. 35(2014), pp. 997-1018 (DOI) (arXiv)
  • F. Tudisco, C. Di Fiore and E. E. Tyrtyshnikov
    Optimal rank matrix algebras preconditioners 
    Linear Algebra Appl. 438(2013), pp. 405-427 (DOI) (arXiv)
  • F. Tudisco and C. Di Fiore
    A preconditioning approach to the pagerank computation problem
    Linear Algebra Appl. 435(2011), pp. 2222-2246 (DOI)

>>>>>>> .r459