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CHarML

Our scientific interests focus on harmonic analysis, inverse problems, PDE and machine learning according to the following belief:

The analysis of massive, high-dimensional, noisy, time-varying data sets has become a critical issue for a large number of scientists and engineers. Major theoretical and algorithmic advances in analyzing massive and complex data are crucial, including methods of exploiting sparsity, clustering and classification, data mining, anomaly detection, and many more.

In the last decade we have witnessed significant advances in many individual core areas of data analysis, including machine learning, signal processing, statistics, optimization, and of course harmonic analysis. It appears highly likely that the next major breakthroughs will occur at the intersection of these disciplines (from Applied Harmonic Analysis, Massive Data Sets, Machine Learning, and Signal Processing).

Background image of the Needle tower by Kenneth Snelson at Kröller-Müller Museum

People

  • Giovanni S.
    Alberti

  • Filippo
    De Mari

  • Ernesto
    De Vito

  • Matteo
    Santacesaria

  • Elena
    Rizzo

  • Alessandro
    Felisi

  • Işıl
    Guleken

  • Paolo
    Angella

  • Simone
    Sanna

  • Shiwei
    Sun

  • Romain
    Petit

  • Anupam
    Gumber

  • Markus
    Holzleitner

  • Dennis
    Elbrächter

  • Edgar
    Desainte-Marév…

  • Sara
    Farinelli

Past People

People
  • Silvia Sciutto | 2020 → 2023 | PhD student | Inverse Problems

  • Lorenzo Sacchi | 2023 | Student

  • Luca Ratti | 2020 → 2023 | Post-doctoral fellow | Inverse Problems and Machine Learning

  • Simone Sanna | 2023 | Student

  • Camilla Casaleggi | 2023 | Student |

  • Camilla Casaleggi | 2022 | Student |

  • Salvatore Ivan Trapasso | 2020 → 2022 | Post-doctoral fellow

  • Luca Wellmeier | 2022 | Student |

  • Matteo Monti | 2019 → 2022 | PhD student | Harmonic Analysis

  • Stefano Vigogna | 2019 → 2021 | PhD student | Harmonic Analysis

  • Simone Sanna | 2021 | Student | Compressed Sensing

  • Geraldo Macoj | 2021 | Student | Machine Learning

  • Beatrice Ravera | 2021 | Student | Analysis

  • Lorenzo Bozzi | 2021 | Student | Analysis

  • Silvia Sciutto | 2020 | Student | Signal Analysis

  • Giuseppe Carta | 2020 | Student | Analysis

  • Ángel Arroyo | 2019 → 2020 | Post-doctoral fellow | Inverse problems

  • Filippo Papallo | 2020 | Student | Analysis

  • Giulia Bollo | 2020 | Student | Machine Learning

  • Francesca Bartolucci | 2020 | PhD student | Harmonic Analysis

  • Davide Parodi | 2019 | Student | Machine Learning & Signal Analysis

  • Marco Baracchini | 2019 | Student | Analysis & Inverse Problems

  • Eugenio Dellepiane | 2019 | Student | Analysis

  • Paolo Campodonico | 2019 | Student | Analysis & Inverse Problems

  • Mattia Barisone | 2019 | Student | Signal Analysis

  • Nicolò Pagliana | 2018 | Student | Machine Learning

  • Silvia Sciutto | 2018 | Student | Analysis & Measure Theory

  • Sandra Albani | 2018 | Student | Signal Analysis

  • Nicola Raffo | 2018 | Student | Signal Analysis

  • Anton Emelchenkov | 2016 | Student | Machine Learning for Inverse Problems

  • Arianna Romani | 2016 | Student | Harmonic Analysis

  • Giulia Vignola | 2014 | Student | Signal Analysis

  • Elisa Businelli | 2014 | Student | Harmonic Analysis

  • Lucia Mantovani | 2013 | PhD student | Harmonic Analysis

  • Manuela Barone | 2013 | Student | Signal Analysis

  • Laura Gemme | 2012 | Student | Machine Learning

  • Ilaria Giulini | 2012 | Student | Probability

  • Francesca Dotti | 2012 | Student | Machine Learning

  • Guido Cesare | 2011 | PhD student | Machine Learning

  • Umberto De Giovannini | 2008 | Student | Machine Learning

  • Irene Venturi | 2008 | PhD student | Harmonic Analysis

  • Paolo Albini | 2007 | PhD student | Quantum Mechanics

  • Giuseppe Zampogna | 2005 | Student

  • Alessandro Ottazzi | 2004 | PhD student | Harmonic Analysis

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    Research projects

    Most recent CHarML research projects

    • Sample complexity for inverse problems in PDE

      Unit CHarML
      Leading scientist Giovanni S. Alberti
      Role within the project Principal Investigator
      Duration 2022 - 2027
      Sponsors EU | ERC StG
      Total funding 1.15 M€
    • CLOSED

      Compressed sensing for inverse problems in PDE

      Unit CHarML
      Leading scientist Giovanni S. Alberti
      Role within the project Principal Investigator
      Duration 2021 - 2023
      Sponsors UniGe
      Total funding 85 k€
    • CLOSED

      Machine Learning for Inverse Problems

      Unit CHarML
      Leading scientist Giovanni S. Alberti, Matteo Santacesaria
      Role within the project co-Principal Investigator
      Duration 2020 - 2023
      Sponsors AFOSR
      Total funding 220 k€
    • CLOSED

      Infinite-dimensional inverse problems with finite measurements

      Unit CHarML
      Leading scientist Giovanni S. Alberti
      Role within the project Principal Investigator
      Duration 2019 - 2021
      Sponsors UniGe Starting grant
      Total funding 59.5 k€

    Publications

    Most recent CHarML publications

    TitleYearAuthorVenue
    Continuous wavelet frames on the sphere: The group-theoretic approach revisited9999Dahlke S.; De Mari F.; De Vito E.; Hansen M.; Hasannasab M.; Quellmalz M.; Steidl G.; Teschke G.APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
    Market areas in general equilibrium2023Lanzara G.; Santacesaria M.JOURNAL OF ECONOMIC THEORY
    Inverse problems on low-dimensional manifolds2023Alberti G.; Arroyo A.; Santacesaria M.NONLINEARITY
    Short Communication: Localized Adversarial Artifacts for Compressed Sensing MRI2023Alaifari Rima; Alberti Giovanni S.; Gauksson TandriSIAM JOURNAL ON IMAGING SCIENCES
    Neural networks for classification of strokes in electrical impedance tomography on a 3D head model2022Candiani V.; Santacesaria M.MATHEMATICS IN ENGINEERING