Xavier Luciani's home page

Doctor in Signal Processing

Curriculum Vitae (in french) - Ph.D. Thesis (in french)

Short Biography

Xavier Luciani was born in Toulon, France. In 2003 he received both the Engineering Diploma from ISEN (Institut Supérieur de l'Electronique et du Numérique), Toulon and a Master's Degree in signal processing from the University of Toulon. He received his Doctorate Degree from the University of Toulon in 2007 (PROTEE laboratory). In 2006-2007, he was Attaché Temporaire d'Enseignement et de Recherche at the University of Toulon. From march 2008 to october 2010, he held two successive postdoctoral positions at the I3S Laboratory (University of Nice Sophia-Antipolis and CNRS) and then at the LTSI Laboratory (University of Rennes 1 and INSERM). From november 2010 to september 2011 he was Attaché Temporaire d'Enseignement et de Recherche at the University of Nice Sophia-Antipolis (teaching) and with the I3S Laboratory (research). From november 2011 to october 2012 he held a post doctoral position at the PROTEE laboratory. Its main research interests have been in signal processing and tensor analysis, especially for blind source separation, inverse problems and fluorescence spectroscopy.

Research interests
    • Tensor decompositions (algorithms and applications)
    • Inverse problems
    • Blind Identification of underdetermined mixtures and Blind Source Separation
    • Joint diagonalization algorithms
    • Signal processing of fluorescence spectra

    Publications liste


    From 2003 to 2011, Université du Sud Toulon Var (UFR science),  Institut Supérieur d'Electronique et du Numérique (ISEN, engineering school), IUT GEII (Toulon), IUT R&T (Nice / Sophia-Antipolis).
    • Electronics (148.5h)
    • Telecommunications (60h)
    • Signal and electrical circuit (44.5h)
    • Logic (36h)
    • Signal and Image processing  (27h)
    • Computting (24h)
    • Mathematics (24h)
    • Physics (9h)

    Matlab codes
    • Tensor package : Various algorithms for the Canonocal Decomposition (CanD or PARAFAC), including Enhanced Line Search.
    • Algorithms for blind identification based on the characteristic function.
    • Others BI/BSS algorithms based on tensor decompositions.
    • Algorithms for Joint Eigenvalue Decomposition (JDTM, JET-O and JET-U)

    Links and Collaborations