Dipartimento di Matematica e Fisica

Hadrontherapy with hElium and protons as Advanced Radiotherapy Treatment for BrEAst Tumors (HEARTBEAT)

Responsabile: Lorenzo Manti
Settore ERC: PE3_16; LS4_12
Data inizio: gen-26
Data fine: dic-28
Ente finanziatore: Istituto Nazionale di Fisica Nucleare (INFN)
Sedi partner: Università di Roma Tre; Università di Roma Tor Vergata; Università di Pavia; INFN LNS Catania; INFN LNL Legnaro; CNAO Pavia
Pagina web del progetto:
Breve descrizione:
The project investigates advanced hadrontherapy approaches for breast cancer treatment using proton and helium ion beams. It aims to demonstrate that the ballistic precision of protons' inverse dose-depth profile allows greater dose sparing to cardiac cells compared to conventional photon radiotherapy, and that helium ion beams offer additional advantages in local tumour control due to their greater biological effectiveness.

Medical Device Maintenance with Artificial Intelligence (MEDMAI)

Responsabile: Stefano Marrone
Settore ERC: PE6_7; PE6_11
Data inizio: 01/06/2025
Data fine: 31/05/2028
Ente finanziatore: MIMIT
Sedi partner: D&D Automazione; Meetweb; Unicampania
Pagina web del progetto:
Breve descrizione:
MEDMAI develops an innovative platform integrating IoT sensors, continuous monitoring systems and AI algorithms to enable predictive and proactive maintenance of medical devices. The system collects operational data via dedicated IoT gateways, detects anomalies, predicts potential failures, and manages spare components via RFID-enabled smart storage. All data is integrated into a centralised platform with a data warehouse and decision support systems to reduce operational costs and extend equipment lifecycle.

Smart IoT Anesthesia Cart & Cabinet (MISTICA)

Responsabile: Laura Verde
Settore ERC: PE6_7; PE6_11
Data inizio: 01/10/2024
Data fine: 30/09/2027
Ente finanziatore: MIMIT
Sedi partner: SANTEC; MEDIACOM; MEDITEL; Dipartimento Multidisciplinare di Specialità Medico-Chirurgiche e Odontoiatriche e Dipartimento della Donna, del Bambino e di Chirurgia Generale e Specialistica – Università degli Studi della Campania 'Luigi Vanvitelli'
Pagina web del progetto:
Breve descrizione:
The MISTICA project develops an integrated IoT, AI and big data platform to improve the safety and efficiency of anaesthetic drug management in operating theatres. The solution includes smart cabinets and carts for automated access control and stock tracking, integrated with hospital information systems and a Clinical Decision Support System for real-time monitoring of drug administration and patient risk, aiming to reduce medication errors and prevent drug misuse.

Anomalies in partial differential equations and applications

Responsabile: Biagio Cassano
Settore ERC: PE1_11
Data inizio: feb-25
Data fine: feb-27
Ente finanziatore: MUR
Sedi partner: Università di Bari; Università di Ferrara; Università di Torino; Università di Bologna
Pagina web del progetto:
Breve descrizione:
The project focuses on partial differential equations that exhibit irregular, degenerate, or unexpected behaviour — so-called anomalies. It explores advances in the analysis of such equations using tools from Fourier, geometric, and phase space analysis, covering topics such as nonlinear evolution equations, spectral asymmetries, stochastic PDEs, and pseudodifferential operators on Lie groups.

Spatio-temporal Functional Marked Point Processes for probabilistic forecasting of earthquakes

Responsabile: Elvira Romano
Settore ERC: PE1_14; PE1_13; SH7_10 GIS
Data inizio: feb-25
Data fine: feb-27
Ente finanziatore: MUR
Sedi partner: Istituto Nazionale di Geofisica e Vulcanologia (INGV) Palermo; Università degli Studi di Palermo
Pagina web del progetto:
Breve descrizione:
The project develops and tests advanced stochastic models to improve earthquake prediction accuracy. The approach integrates detailed seismic event information such as waveforms and local spatio-temporal features using Functional Marked Point Process models and Conformal Prediction methods to quantify uncertainty and generate reliable prediction sets without relying on strict distributional assumptions.

Primary spectrometric thermometry for gases (PRISPECTEMP)

Responsabile: Antonio Castrillo
Settore ERC: PE2_10 Atomic, molecular physics; PE2_17 Metrology and measurement
Data inizio: 01/09/2023
Data fine: 31/08/2026
Ente finanziatore: EURAMET
Sedi partner: PTB (Germany, Coordinator); CEM (Spain); DFM (Denmark); JV (Norway); TUBITAK (Turkey); VTT (Finland); DLR (Germany); Iberoptics (Spain); RUG (Netherlands); UCM (Spain); UH (Finland); UMK (Poland); UCL (United Kingdom)
Pagina web del progetto: https://www.prispectemp.ptb.de/home
Breve descrizione:
The project expands spectroscopic gas thermometry capabilities by developing Rotational-Vibrational Spectroscopic Gas Thermometry (RVSGT) for new sensor molecules including CO, CO₂ and O₂, targeting a primary measurement uncertainty of 25 mK. The methodology is cross-validated against Doppler broadening thermometry and two-line laser thermometry, enabling more accurate remote temperature measurements for climate observation and emission surveillance.

Partial Differential Equations: reaction-diffusion, integro-differential, and mathematical physics problems

Responsabile: Biagio Cassano
Settore ERC: PE1_11; PE1_12
Data inizio: set-22
Data fine: ago-26
Ente finanziatore: Ministerio de Ciencia e Innovación, Gobierno de España
Sedi partner: Universitat Politècnica de Catalunya
Pagina web del progetto:
Breve descrizione:
This research group focuses on the analysis of PDEs and related areas of mathematical analysis, including reaction-diffusion and nonlocal fractional equations, kinetic and aggregation-diffusion models, and spectral theory of differential operators. Applications range from inverse problems and many-body quantum systems to biology, social sciences, and robotics.

Algebraic and Geometric methods in coding theory

Responsabile: Ferdinando Zullo
Settore ERC: PE1_14; PE6_6
Data inizio: gen-24
Data fine: giu-26
Ente finanziatore: French Embassy in Italy and Laboratory Ypatia of Mathematical Sciences, CNRS/INdAM
Sedi partner: Université Paris 8
Pagina web del progetto:
Breve descrizione:
The project advances coding theory and network coding by combining tools from algebra, geometry, combinatorics, information theory, and computer science. It focuses on codes endowed with Hamming, rank, sum-rank and subspace metrics, with objectives including the study of minimal codewords, rank and sum-rank analogues of group codes, efficient encoding and decoding algorithms, and the design of code-based cryptographic schemes.

Einstein Telescope Infrastructure Consortium (ETIC)

Responsabile: Livio Gianfrani
Settore ERC: PE9 Universe Sciences
Data inizio: 01-gen-23
Data fine: 30-apr-26
Ente finanziatore: Unione Europea e MUR-PNRR
Sedi partner: INFN e altri co-applicanti (https://www.einstein-telescope.it/)
Pagina web del progetto: https://web.infn.it/einsteintelescope/index.php/it/home-it-it
Breve descrizione:
The Einstein Telescope (ET) is a 3rd generation Gravitational Wave observatory entered in the ESFRI roadmap 2021. ETIC aims to form the Italian network of laboratories needed to develop ET technologies and define the key elements of its technical and engineering design. The project addresses environmental, architectural, infrastructural and socio-economic aspects to support the feasibility study for the ET infrastructure in Sardinia, aggregating advanced expertise in GW physics, engineering and architecture across national research institutions and universities.

MEtrology and Nonlinear optics for Precision muonic HYdrogen physicS (MENPHYS)

Responsabile: Livio Gianfrani
Settore ERC: PE2_10 Atomic, molecular physics; PE2_14 Lasers, ultra-short lasers and laser physics
Data inizio: 28-set-23
Data fine: 28-feb-26
Ente finanziatore: MUR – PRIN framework
Sedi partner: CNR - Istituto Nazionale di Ottica; INFN - Sezione di Trieste; Università di Pavia
Pagina web del progetto:
Breve descrizione:
The MENPHYS project aims to boost the capabilities of the FAMU (Fisica degli Atomi MUonici) collaboration, which is conducting an experiment for the first hyperfine splitting measurement of the muonic hydrogen ground state at the Rutherford-Appleton Laboratory (RAL), UK. The project strengthens the FAMU experiment by upgrading the laser system near 6.8 μm, simplifying the coupling of laser light into the optical cavity, increasing accuracy in ethylene transition frequency determination, and providing a reliable strategy for online absolute frequency calibration of the excitation laser.

Non linear models for magma transport and volcanoes generation

A multidisciplinary approach to evaluate ecosystems resilience under climate change (MATFORPAT)

Responsabile locale: Gerardo Toraldo
Settore ERC: PE1_21 Application of mathematics in sciences
Data inizio: 30/11/2023
Data fine: 28/02/2026
Ente finanziatore: MUR
Sedi partner: Università di Messina; Università di Napoli Federico II
Pagina web del progetto: https://www.matforpat.com/
Breve descrizione:
The project builds a comprehensive framework combining applied mathematics, numerical analysis, computer science, and ecology to better predict ecosystem transitions and measure resilience under climate change. By integrating satellite imagery, machine learning, mathematical models, and ecological indicators, it analyses vegetation patterns, develops parameter identification algorithms, and simulates potential ecosystem collapse scenarios in dryland ecosystems.

Numerical Optimization with Adaptive Accuracy and Applications to Machine Learning (2022N3ZNAX)

Responsabile locale: Gerardo Toraldo
Settore ERC: PE1 Mathematics
Data inizio: 28/09/2023
Data fine: 28/02/2026
Ente finanziatore: MUR
Sedi partner: Università di Modena e Reggio Emilia; Università di Napoli Federico II; Università di Firenze
Pagina web del progetto: https://www.dma.unina.it/NOA2MLprin2022/
Breve descrizione:
The project develops a unified framework of optimization algorithms to efficiently tackle large-scale problems involving massive datasets, high dimensionality, uncertainty, and non-convexity. It is organized around adaptive stochastic methods, inexact deterministic methods, and optimization for scientific machine learning, with a key goal of reducing computational cost and carbon footprint. Target applications include security, energy, agriculture, healthcare, and finance.

Stochastic Models in Biomathematics and Applications (PRIN2022-PNRR P2022XSF5H)

Responsabile: Enrica Pirozzi
Settore ERC: PE1_21 Application of mathematics in sciences
Data inizio: 30-nov-23
Data fine: 28-feb-26
Ente finanziatore: MUR
Sedi partner: Università di Salerno; Università della Basilicata
Pagina web del progetto:
Breve descrizione:
The project contributes to the development of mathematical methods for the analysis and simulation of biological systems subject to random perturbations. Activities focus on analytical and stochastic methods for biomathematical modelling, fractional calculus tools for solving evolution equations governing probability distributions, and the development of simulation algorithms for stochastic processes that model biological systems with memory effects.

Exploiting separation of scales in nuclear structure and dynamics

Responsabile locale per Università Luigi Vanvitelli: Luigi Coraggio
Settore ERC: PE2_1; PE2_6; PE2_7
Data inizio: 28/09/2023
Data fine: 28/02/2026
Ente finanziatore: MUR
Sedi partner: Università di Pisa; Università della Campania; Università del Salento
Pagina web del progetto:
Breve descrizione:
The project develops nuclear Hamiltonians within low-energy effective field theories (LEEFT) to calculate nuclear matrix elements relevant for beyond-the-standard-model phenomena such as neutrinoless double-beta decay and dark matter searches. Work includes deriving subleading three-nucleon interactions, electroweak transition operators, shell-model studies of nuclei up to A=100, infinite nuclear matter equations of state, and the investigation of halo nuclei structure and electromagnetic responses.

A mathematical approach to inverse problems arising in cultural heritage preservation and dissemination

Responsabile: Ferdinando Zullo
Settore ERC: PE1_16; PE1_14; PE6_8; PE6_9; SH6_3
Data inizio: nov-23
Data fine: feb-26
Ente finanziatore: MUR
Sedi partner: Università degli Studi di Cagliari; ICAR-CNR
Pagina web del progetto:
Breve descrizione:
The project provides new scientific solutions for cultural heritage preservation and dissemination through two main contributions: non-invasive and low-cost methods for identifying archaeological sites using geophysical properties of the ground, supported by new mathematical models and regularization algorithms; and automatic software tools for analysing artefacts, constructing three-dimensional models via photometric stereo and stereo-vision, and extracting glyphs and incisions for study and public dissemination.

Privacy and Blockchain in Public Integrated Filing systems (PaB-PIF)

Responsabile: Mauro Iacono
Settore ERC: PE6_2; PE6_5
Data inizio: 01/01/2024
Data fine: 31/01/2026
Ente finanziatore: MUR
Sedi partner: Università degli Studi di Messina
Pagina web del progetto: https://pab-pif.unime.it
Breve descrizione:
The PaB-PIF project defines a reference architecture for implementing efficient, secure and GDPR-compliant systems for managing personal data in contexts where public and private entities collaborate. It focuses on blockchain technology as the most suitable solution for supporting heterogeneous environments in which institutions with potentially conflicting interests must interact.

Sviluppo di Algoritmi Quantistici di Machine Learning per problemi di classificazione di immagini (QUANTIC)

Responsabile: Luigi Coraggio
Settore ERC: PE2
Data inizio: 02/01/2025
Data fine: 30/11/2025
Ente finanziatore: Spoke 8 - NQSTI
Sedi partner: NetCom
Pagina web del progetto:
Breve descrizione:
The project develops and implements Quantum Machine Learning (QML) models for image classification problems, comparing their performance with classical models in terms of accuracy, computational resource requirements, and scalability. As a case study, it focuses on the classification of hazelnut plant varieties, phytopathologies and nutritional deficiencies through leaf image analysis, contributing to the broader understanding of QML applicability to practical industrial scenarios.

Green Growth Indicators Development and Analysis

Responsabile: Rosanna Verde
Settore ERC: —
Data inizio: mag-24
Data fine: nov-25
Ente finanziatore: PNRR
Sedi partner:
Pagina web del progetto: https://grins.it/
Breve descrizione:
The project focuses on the development and analysis of statistical indicators for measuring green growth and environmental sustainability. The research activities aim to design methodologies for monitoring the environmental and economic performance of territories and economic sectors, with particular attention to the integration of environmental, economic and social dimensions of sustainable development. The indicators developed within the project contribute to supporting evidence-based policies and strategies aligned with the objectives of the European Green Deal and the National Recovery and Resilience Plan (PNRR).

MPM-4-ASE - Monitoring and Predictive Models for Assessing the Sustainability of Economic Activities in Southern Italy

Responsabile: Rosanna Verde
Settore ERC: —
Data inizio: mag-24
Data fine: ott-25
Ente finanziatore: PNRR
Sedi partner:
Pagina web del progetto: https://grins.it/
Breve descrizione:
The project develops monitoring systems and predictive statistical models for assessing the sustainability of economic activities in Southern Italy. The research focuses on the construction of indicators and data-driven models aimed at analysing the environmental, economic and social impacts of production systems. The results support the evaluation of sustainable development policies and contribute to the objectives of the GRINS ecosystem within the Italian National Recovery and Resilience Plan (PNRR).

PNRR MNESYS

Testing the potential impact of foreshocks (PRIN 2022 PNRR P202247YK)

Sistema di Supporto Decisionale per la diagnosi precoce e il follow-up di pazienti affetti da Valvole Uretrali Posteriori (SUD4VUP)

Responsabile: Laura Verde
Settore ERC: PE6_7; PE6_11
Data inizio: 10-giu-24
Data fine: 31-ago-25
Ente finanziatore: MUR - PNRR
Sedi partner: Dipartimento della Donna, del Bambino, di Chirurgia Generale e Specialistica – Università degli Studi della Campania 'Luigi Vanvitelli'
Pagina web del progetto: https://www.sud4vup.it/
Breve descrizione:
The SUD4VUP project develops a decision support system for the early diagnosis and monitoring of paediatric patients with posterior urethral valves (PUVs). The system integrates clinical, anthropometric, anamnestic and instrumental data via multimodal analysis, and uses Explainable Artificial Intelligence (XAI) techniques to provide specialist physicians with transparent diagnostic decision-making support.

Control of quantum systems described by the Dirac equation

Responsabile: Biagio Cassano
Settore ERC: PE1_11; PE1_19
Data inizio: lug-24
Data fine: lug-25
Ente finanziatore: Natural Sciences and Engineering Research Council of Canada
Sedi partner: University of Waterloo (Canada)
Pagina web del progetto:
Breve descrizione:
This project investigates controllability and stabilization properties of relativistic quantum systems governed by the Dirac equation. It focuses on boundary and distributed control mechanisms, spectral properties of Dirac operators, and the impact of external electromagnetic fields, developing rigorous mathematical frameworks for exact and approximate controllability under relativistic effects.

Quantum Machine Learning Algorithms for Nuclear Theory and Edge Detection (QML-NTED)

Responsabile: Luigi Coraggio
Settore ERC: PE2
Data inizio: 01/05/2024
Data fine: 31/07/2025
Ente finanziatore: Spoke 10-ICSC
Sedi partner: Unicampania
Pagina web del progetto:
Breve descrizione:
The project explores and develops Quantum Machine Learning (QML) algorithms for Nuclear Theory (NT) and Edge Detection (ED) problems, leveraging quantum properties such as entanglement and superposition to process information beyond classical capabilities. It analyses the performance of quantum algorithms compared to classical counterparts and discusses the challenges and future prospects of QML in the context of current quantum technology limitations.

Functional encryption per cifrature per cloud

Responsabile: Antonio Tortora / Ferdinando Zullo
Settore ERC: PE1
Data inizio: 19/07/2023
Data fine: 19/07/2025
Ente finanziatore: Fondazione Bruno Kessler
Sedi partner: Università di Bari; Università dell'Aquila; Università di Napoli Federico II; Università di Perugia; Università di Roma Tre; Università di Salerno
Pagina web del progetto:
Breve descrizione:
Progetto di ricerca commissionato dalla Presidenza del Consiglio dei Ministri alla Fondazione Bruno Kessler, finalizzato all'individuazione di algoritmi di cifratura idonei alla protezione delle informazioni. Le attività hanno riguardato la definizione dello stato dell'arte della Functional Encryption (FE), la scelta di famiglie di protocolli FE adatte a scenari di Cloud Encryption, la sperimentazione dei protocolli individuati e l'individuazione di possibili suite di protocolli FE.

Mathematical Modeling of Viscoelastic Tissues for Cervical Cancer Treatment (VISCOMATH)

Responsabile: Alfonsina Tartaglione
Settore ERC: PE1_12 Mathematical Physics
Data inizio: 01/09/2024
Data fine: 28/02/2025
Ente finanziatore: Unicampania D.R. 111/2024
Sedi partner: Dipartimento di Medicina di Precisione – Unicampania
Pagina web del progetto:
Breve descrizione:
The VISCOMATH project investigates the mechanical properties of biological tissues within the framework of viscoelasticity, with a focus on developing mathematical models for vaginal dilation in the context of radiation-induced vaginal stenosis. The research addresses the viscoelastic properties of vaginal tissues and the regularity properties of solutions to Navier-Stokes and Navier-Stokes-Fourier equations for both incompressible and compressible viscous fluids.

HARvesters MOdelled by Nonlinear ordinarY differential equations (HARMONY)

Responsabile: Adele Ferone
Settore ERC: PE1
Data inizio: 01/09/2024
Data fine: 28/02/2025
Ente finanziatore: Unicampania D.R. 111/2024
Sedi partner: Dipartimento di Ingegneria – Unicampania
Pagina web del progetto: https://www.matfis.unicampania.it/ricerca/progetti-di-ricerca#harmony-harvesters-modelled-by-nonlinear-ordinary-differential-equations
Breve descrizione:
The project focuses on Vibration Energy Harvesters (VEHs) as an eco-friendly solution for supplying low-power smart electronic systems in Internet of Things (IoT) applications, modelling their behaviour through nonlinear ordinary differential equations.

Dynamical Analysis of Interacting biological SYstems through statistics (DAISY)

Responsabile: Emma D'Aniello
Settore ERC: PE1_8; LS8_10; PE1_14; PE1_13; PE6_14
Data inizio: 01/09/2024
Data fine: 28/02/2025
Ente finanziatore: Università Vanvitelli D.R. 111/2024
Sedi partner: Dipartimento di Scienze e Tecnologie Ambientali, Biologiche e Farmaceutiche (DiSTABiF) – Università Vanvitelli
Pagina web del progetto:
Breve descrizione:
The project deepens understanding of mathematical problems with applications in biology, focusing on the long-term behaviour of discrete and continuous dynamical systems, attractors and chaotic behaviours, properties of Koopman operators, and stochastic models for neuronal and biological dynamics using fractional calculus and functional data analysis.

Progetti di Ricerca