Matteo Nori

Fellow
Knowledge groupGovernment, Health and Not for Profit
Research domainsSpace Economy
Teaching domainsBig & Small Data, Data Analysis Process, Descriptive Analytics, Time Series Analysis, Predictive Analytics
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Biography

Matteo Nori is an astrophysicist with extensive expertise in data science and analysis, specialized in the physical and statistical modelling of complex systems. He holds a double MSc degree from Sorbonne University (France) and Politecnico di Torino (Italy), earned in July 2015, and completed his PhD in Astrophysics at Alma Mater Studiorum University of Bologna (Italy) in March 2019. 

From 2019 to 2023, Matteo Nori served as a researcher at Bologna University and as a Postdoctoral Associate at New York University Abu Dhabi (UAE). During these years, he pursued in his investigation of the physical models of Dark Matter and Dark Energy and their implications for galaxy formation and evolution through numerical means. 

Matteo Nori is collaborating with the SEE Lab since February 2024. Thanks to his scientific and technical skills, he is involved both in the research efforts, in particular revolving around numerical simulations and projections of present and future satellite populations, as well as in the design, development and automatization of the data analysis of the SEEData dataset.

Recent Publications

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  • 2024
    No Catch-22 for fuzzy dark matter: testing substructure counts and core sizes via high-resolution cosmological simulations
    ELGAMAL, S., M. NORI, A. V. MACCIÒ, M. BALDI, S. WATERVAL, "No Catch-22 for fuzzy dark matter: testing substructure counts and core sizes via high-resolution cosmological simulations", Monthly Notices of the Royal Astronomical Society, 2024, vol. 532, no. 4, pp. 4050-4059
  • 2023
    Fuzzy Aquarius: evolution of a Milky-way like system in the Fuzzy Dark Matter scenario
    NORI, M., A. V. MACCIÒ, M. BALDI, "Fuzzy Aquarius: evolution of a Milky-way like system in the Fuzzy Dark Matter scenario", Monthly Notices of the Royal Astronomical Society, 2023, vol. 522, no. 1, pp. 1451-1463
  • 2022
    NIHAO – XXVIII. Collateral effects of AGN on dark matter concentration and stellar kinematics
    WATERVAL, S., S. ELGAMAL, M. NORI, M. PASQUATO, A. V. MACCIÒ, M. BLANK, K. L. DIXON, X. KANG, T. IBRAYEV, "NIHAO – XXVIII. Collateral effects of AGN on dark matter concentration and stellar kinematics", Monthly Notices of the Royal Astronomical Society, 2022, vol. 514, no. 4, pp. 5307-5319
  • 2022
    Sparse Identification of Variable Star Dynamics
    PASQUATO, M., M. ABBAS, A. A. TRANI, M. NORI, J. A. KWIECINSKI, P. TREVISAN, V. F. BRAGA, G. BONO, A. V. MACCIÒ, "Sparse Identification of Variable Star Dynamics", The Astrophysical Journal Supplement, 2022, vol. 930, no. 2, pp. 161
  • 2020
    Dynamic zoom simulations: A fast, adaptive algorithm for simulating light-cones
    GARALDI, E., M. NORI, M. BALDI, "Dynamic zoom simulations: A fast, adaptive algorithm for simulating light-cones", Monthly Notices of the Royal Astronomical Society, 2020, vol. 499, no. 2, pp. 2685-2700
  • 2020
    Scaling relations of fuzzy dark matter haloes – I. Individual systems in their cosmological environment
    NORI, M., M. BALDI, "Scaling relations of fuzzy dark matter haloes – I. Individual systems in their cosmological environment", Monthly Notices of the Royal Astronomical Society, 2020, vol. 501, no. 1, pp. 1539-1556