Matteo Ciferri

PhD Student

matteociferri.1995@gmail.com

Biography

Matteo Ciferri is a student in the National Ph.D. Program in Artificial Intelligence at the Tor Vergata Medical Physics Section.
He holds a master’s degree in Management Engineering from La Sapienza University in Rome, with a focus on data science and optimization models. 
His interests include neural networks, deep learning, data mining, and audio programming.

Last 5 articles (Scopus)

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Reconstructing music perception from brain activity using a prior guided diffusion model; Scientific Reports; December 2025; DOI: 10.1038/s41598-025-26095-w
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Optimal Transport and Contrastive Learning for Brain Decoding of Musical Perception; Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference; 1 July 2025; DOI: 10.1109/EMBC58623.2025.11253498
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Last 5 articles (PubMed)

  • Optimal Transport and Contrastive Learning for Brain Decoding of Musical Perception
    on 3 December 2025

    Brain decoding aims to reconstruct external stimuli from brain activity, providing insights into the neural representation of cognitive experiences. Music decoding from functional magnetic resonance imaging (fMRI) is particularly challenging due to the complexity of auditory processing and the temporal limitations of fMRI signals. In this study, we introduce a novel decoding framework that improves the alignment between fMRI activity and latent musical representations extracted using a...

  • Reconstructing music perception from brain activity using a prior guided diffusion model
    on 26 November 2025

    Reconstructing music directly from brain activity provides insight into the neural representations underlying auditory processing and paves the way for future brain-computer interfaces. We introduce a fully data-driven pipeline that combines cross-subject functional alignment with bayesian decoding in the latent space of a diffusion-based audio generator. Functional alignment projects individual fMRI responses onto a shared representational manifold, increasing the performance of...

  • Impact of the production method on the properties of erythrocyte-derived extracellular particles: a quantitative and qualitative evaluation
    on 10 November 2025

    Red blood cell-derived extracellular particles (RBCEPs) possess many benefits in healthcare applications representing a simple and powerful platform for drug delivery. Nowadays, whether the different methods proposed to produce them could influence their properties remains poorly investigated. We compared three main types of RBCEPs: (i) naturally released during the blood bag storage (EryErythrosomes, EryEs), (ii) produced artificially through RBC sonication (NanoErythrosomes, NanoEs), and (iii)...

  • Timing still matters: Auditory attention and verbal memory in children implanted before versus after age one
    on 19 October 2025

    CONCLUSION: This study emphasized the critical role of early intervention and oral language competence in developing auditory attention and verbal memory skills in CI children. Efforts to ensure timely intervention and empower language skills after cochlear implantation should guide clinicians' decisions and the implementation of habilitative programs.

  • Refining Flow Cytometry-based Sorting of Plasma-derived Extracellular Vesicles
    on 21 August 2025

    CONCLUSIONS: These advancements enable high-purity EV subpopulation isolation, facilitating applications such as identifying cancer biomarkers and developing EV-based targeted therapies.