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Scientific publications

Academic research that becomes a competitive advantage for your business


Scientific publications

Academic research
that becomes a competitive advantage for your business


Scientific publications

Academic research that becomes a competitive advantage for your business

Quantum computing
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From graphs to qubits: a critical review of quantum graph neural networks
September 11, 2026
Quantum Graph Neural Networks merge relational learning with quantum computing to explore new paths toward more efficient AI.
A. Ceschini, F. Mauro, F. De Falco, A. Sebastianelli, A, Verdone, A. Rosato, B. Le Saux, M. Panella, P. Gamba, S. L. Ullo
Renewable energy
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A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data
March 14, 2026
A KDD-driven pipeline turns smart meter streams into multi-step load forecasts, benchmarking feature reduction and models.
F. De Caro, A. Andreotti, R. Araneo, M. Panella, A. Rosato, A. Vaccaro, D. Villaci
Quantum computing
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Risc-v isa extensions with hardware acceleration for hyperdimensional computing
May 15, 2025
RISC-V hardware acceleration makes hyperdimensional computing up to 2665× faster while preserving flexibility and programmability.
R. Martino, M. Angioli, A. Rosato, M. Barbirotta, A. Cheikh, M. Olivieri
Biomedical
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Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks
December 5, 2024
A deep learning model enhances early autism diagnosis by analyzing visual patterns with eye tracking.
F. Colonnese, F. Di Luzio, A. Rosato, M. Panella
Quantum computing
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Quantum Generative Modeling via Straightforward State Preparation
November 30, 2024
A lightweight quantum generative model creates high-fidelity data samples with minimal parameters and efficient state preparation.
L. Lavagna, F. De Falco, S. Piperno, A. Ceschini, A. Rosato, M. Panella
Quantum computing
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Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization
November 29, 2024
A novel quantum-classical algorithm boosts QAOA performance with fewer layers, enabling real-world optimization on NISQ devices.
F. De Falco, S. Piperno, L. Lavagna, A. Ceschini, A. Rosato, M. Panella
Renewable energy
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A Deep Learning-based Approach for Battery Life Classification
November 20, 2024
A deep learning-based LSTM network accurately classifies battery health, optimizing energy storage and predictive maintenance.
F. Succetti, A. Dell’Era, A. Rosato, A. Fioravanti, R. Araneo, M. Panella
Biomedical
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An explainable fast deep neural network for emotion recognition
November 14, 2024
A fast, explainable deep neural network enhances emotion recognition by optimizing facial landmark analysis.
F. Di Luzio, A. Rosato, M. Panella
Quantum computing
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Evolving Hybrid Quantum-Classical GRU Architectures for Multivariate Time Series
November 4, 2024
QGRU combines quantum circuits with recurrent learning to forecast complex time series with fewer parameters and faster computation.
F. De Falco, L. Lavagna, A. Ceschini, A. Rosato, M. Panella
Renewable energy
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Multi-label classification with imbalanced classes by fuzzy deep neural networks
October 18, 2024
A fuzzy deep neural network accurately classifies household appliances in real time using symbolic data and multi-label AI.
F. Succetti, A. Rosato, M. Panella
Quantum computing
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Quantum enhanced knowledge distillation
October 11, 2024
Classical-to-quantum knowledge distillation boosts hybrid AI performance using efficient quantum circuits and reduced model sizes.
S. Piperno, L. Lavagna, F. De Falco, A. Ceschini, A. Rosato, D. Windridge, M. Panella
Quantum computing
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Q-SCALE: Quantum computing-based Sensor Calibration for Advanced Learning and Efficiency
October 3, 2024
Quantum AI calibrates low-cost air-quality sensors with LSTM-level accuracy using far fewer trainable parameters.
L. Bergadano, A. Ceschini, P. Chiavassa, E. Giusto, B. Montrucchio, M. Panella, A. Rosato
Quantum computing
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A Layerwise-Multi-Angle Approach to Fine-Tuning the Quantum Approximate Optimization Algorithm
September 9, 2024
LMA-QAOA combines layerwise training with multi-angle flexibility to improve quantum optimization accuracy and stability.
L. Lavagna, A. Ceschini, A. Rosato, M. Panella
Quantum computing
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A variational approach to quantum gated recurrent units
August 21, 2024
A faster and efficient Quantum Gated Recurrent Unit (QGRU) improves time series forecasting.
A. Ceschini, A. Rosato, M. Panella
Aerospace
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A Neural Network Symbolic Approach to Structural Health Monitoring in Aerospace Applications
August 8, 2024
A symbolic deep learning approach enhances structural health monitoring in aerospace achieving near-perfect damage classification.
F. Angeletti, F. Succetti, M. Panella, A. Rosato
Advanced AI Methods
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An adaptive embedding procedure for time series forecasting with deep neural networks
September 9, 2023
A novel deep learning model that integrates adaptive embedding with bidirectional LSTMs to enhance time series forecasting.
F. Succetti, A. Rosato, M. Panella
Aerospace
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Multi-Damage Detection in Composite Space Structures via Deep Learning
August 29, 2023
A Bi-LSTM detects and locates debris damage in satellite solar arrays from brief sensor signals.
F. Angeletti, P. Gasbarri, M. Panella, A. Rosato
Advanced AI Methods
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Neural Graphs: an Effective Solution for the Resource Allocation in NFV Sites interconnected by Elastic Optical Networks
August 8, 2023
Neural graphs predict NFV resource demand by learning network topology and time, cutting training time without sacrificing accuracy.
V. Eramo, F. G. Lavacca, F. Valente, V. Filippetti, A. Rosato, A. Verdone
Cybersecurity
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Modular quantum circuits for secure communication
August 2, 2023
Quantum modular circuits enable ultra-secure communication for fast, parallel encryption and decryption.
A. Ceschini, A. Rosato, M. Panella
Cybersecurity
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Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
July 26, 2023
AI turns smart-meter data into autonomous alerts that expose electricity theft while reducing costly manual inspections.
E. Stracqualursi, A. Rosato, G. Di Lorenzo, M. Panella, R. Araneo
Advanced AI Methods
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Perceptron Theory Can Predict the Accuracy of Neural Networks
February 6, 2023
A perceptron-based theory predicts neural network accuracy using output statistics, fast, data-free, and surprisingly precise.
D. Kleyko, A. Rosato, E. Paxon Frady, M. Panella, F. T. Sommer
Renewable energy
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Challenges and perspectives of smart grid systems in islands: a real case study
January 4, 2023
Integrating renewables with AI tools offers sustainable solutions, especially in isolated contexts.
F. Succetti, A. Rosato, R. Araneo, G. Di Lorenzo, M. Panella
Aerospace
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A Study on structural health monitoring of a large space antenna via distributed sensors and deep learning
December 29, 2022
AI-powered Bi-LSTM detect structural damage in flexible satellite antennas with over 99% accuracy using onboard sensor data.
F. Angeletti, P. Iannelli, P. Gasbarri, M. Panella, A. Rosato
Biomedical
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A randomized deep neural network for emotion recognition with landmarks detection
December 6, 2022
Novel randomized DNN uses facial landmarks for fast emotion recognition.
F. Di Luzio, A. Rosato, M. Panella
Renewable energy
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Hybrid Quantum-Classical Recurrent Neural Networks for Time Series Prediction
September 30, 2022
A hybrid quantum-classical recurrent network improves solar power forecasting by combining LSTM memory with quantum layers.
A. Ceschini, A. Rosato, M. Panella
Quantum computing
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All-optical AND Logic Gate Based on Semiconductor Optical Amplifiers for Implementing Deep Recurrent Neural Networks
September 21, 2022
An all-optical AND gate uses semiconductor amplifiers to enable ultrafast photonic recurrent neural networks.
B. Alam, A. Ceschini, A. Rosato, M. Panella, R. Asquini
Hyperdimensional Computing
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Few-shot Federated Learning in Randomized Neural Networks via Hyperdimensional Computing
August 30, 2022
Fast, private AI learning from few examples using hyperdimensional computing and randomized networks across distributed devices.
A. Rosato, M. Panella, E. Osipov, D. Kleyko
Renewable energy
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Multivariate Time Series Analysis for Electrical Power Theft Detection in the Distribution Grid
August 19, 2022
A convolutional neural network analyzes multivariate time series to detect energy theft in distribution grids effectively.
A. Ceschini, A. Rosato, F. Succetti, R. Araneo, M. Panella
Renewable energy
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Nonexclusive Classification of Household Appliances by Fuzzy Deep Neural Networks
July 18, 2022
A fuzzy deep neural network classifies appliances by degrees of membership, embracing uncertainty in energy data.
F. Succetti, A. Rosato, M. Panella
Biomedical
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A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition
July 5, 2022
A fast AI-based approach for Wi-Fi-based human activity recognition achieves real-time, non-invasive monitoring.
F. Succetti, A. Rosato, F. Di Luzio, A. Ceschini, M. Panella
Distributed Learning
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Distributed LSTM-based cloud resource allocation in Network Function Virtualization Architectures
June 18, 2022
Distributed LSTM agents predict cloud resource needs for NFV, reducing overhead while preserving accuracy and privacy.
T. Catena, V. Eramo, M. Panella, A. Rosato
Quantum computing
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Quasi-Chaotic Oscillators Based on Modular Quantum Circuits
April 18, 2022
Quantum modular circuits generate quasi-chaotic signals for future secure, parallel encryption schemes.
A. Ceschini, A. Rosato, M. Panella
Quantum computing
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Design of an LSTM Cell on a Quantum Hardware
November 8, 2021
A quantum circuit design translates LSTM memory gates into qubit-based operations for future quantum recurrent networks
A. Ceschini, A. Rosato, M. Panella
Renewable energy
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Multivariate Prediction of Energy Time Series by Autoencoded LSTM Networks
November 3, 2021
An autoencoded LSTM learns hidden structure in multivariate energy signals to forecast solar power more accurately.
F. Succetti, F. Di Luzio, A. Ceschini, A. Rosato, R. Araneo, M. Panella
Renewable energy
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Deep Neural Networks for Electric Energy Theft and Anomaly Detection in the Distribution Grid
November 3, 2021
A deep Bi-LSTM detects daily energy theft and grid anomalies directly from smart meter time series.
A. Ceschini, A. Rosato, F. Succetti, F. Di Luzio, M. Mitolo, R. Araneo, M. Panella
Hyperdimensional Computing
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Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networks
September 20, 2021
A hyperdimensional compression scheme lets distributed neural agents share classifiers efficiently without sharing raw data.
A. Rosato, M. Panella, D. Kleyko
Renewable energy
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A Blockwise Embedding for Multi-Day-Ahead Prediction of Energy Time Series by Randomized Deep Neural Networks
September 20, 2021
A randomized CNN-LSTM learns energy data in daily blocks to forecast entire future days with high efficiency.
F. Di Luzio, A. Rosato, F. Succetti, M. Panella
Hyperdimensional Computing
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On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks
August 21, 2021
An HDC-based compression method makes distributed classifiers lighter to share while preserving predictive power.
A. Rosato, M. Panella, E. Osipov, D. Kleyko
Aerospace
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Deep learning-based Structural Health Monitoring for damage detection on a large space antenna
August 5, 2021
LSTM networks detect and localize structural damage in large space platforms by learning vibration patterns from sensor data.
P. Iannelli, F. Angeletti, P. Gasbarri, M. Panella, A. Rosato
Distributed Learning
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A decentralized algorithm for distributed ensemble clustering
July 27, 2021
Agents cluster local data and reach global consensus by sharing prototypes, not data, enabling private distributed learning.
A. Rosato, R. Altilio, M. Panella
Renewable energy
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2-D Convolutional Deep Neural Network for the Multivariate Prediction of Photovoltaic Time Series
April 23, 2021
A 2D CNN-LSTM model turns weather and PV data into sharper multivariate solar power forecasts.
A. Rosato, R. Araneo, A. Andreotti, F. Succetti, M. Panella
Renewable energy
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Two-stage dynamic management in energy communities using a decision system based on elastic net regularization
March 31, 2021
A two-stage forecasting-optimization system for efficient management of energy communities.
A. Rosato, M. Panella, A. Andreotti, Osama A. Mohammed, R. Araneo,
Renewable energy
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Two-stage dynamic management in energy communities using a decision system based on elastic net regularization
March 31, 2021
A CNN–LSTM model turns multivariate time series into 2D maps to improve solar power forecasting from weather and sensor data.
A. Rosato, M. Panella, A. Andreotti, Osama A. Mohammed, R. Araneo
Renewable energy
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Deep Neural Networks for Multivariate Prediction of Photovoltaic Power Time Series
November 20, 2020
Deep neural networks enhance photovoltaic power forecasting by leveraging multivariate time-series modelling.
F. Succetti, A. Rosato, R. Araneo, M. Panella,
Efficient Edge AI
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A Parallel Hardware Implementation for 2-D Hierarchical Clustering Based on Fuzzy Logic
October 21, 2020
Energy-aware FPGA architecture enables parallel fuzzy hierarchical clustering for real-time embedded intelligence.
G. C. Cardarilli, L. Di Nunzio, R. Fazzolari, M. Panella, M. Re, A. Rosato
Renewable energy
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Prediction of Photovoltaic Time Series by Recurrent Neural Networks and Genetic Embedding
September 3, 2020
Genetic optimization of time-delay embedding boosts recurrent neural network accuracy for photovoltaic time series forecasting.
A. Rosato, R. Araneo, M. Panella
Efficient Edge AI
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An Energy-Aware Hardware Implementation of 2D Hierarchical Clustering
August 6, 2020
Energy-aware hardware optimizations make 2D hierarchical clustering fast and practical for low-power embedded and edge devices.
G. C. Cardarilli, R. Fazzolari, M. Matta, M. Panella, A. Rosato, S. Spanò
Renewable energy
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A Fuzzy Neural Network Approach to Quality Assessment of Water Reservoirs
March 2, 2020
Satellite imagery and fuzzy neural networks enable accurate estimation of key water quality indicators in large reservoirs.
H. A. N. Silva, A. Rosato, M. Panella
Aerospace
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Retrieving Chlorophyll-a Levels, Transparency and TSS Concentration from Multispectral Satellite Data by Using Artificial Neural Networks
February 19, 2018
AI and satellite data join forces to estimate water quality in Amazon reservoirs with high accuracy and minimal fieldwork.
H. A. Nascimento Silva, G. Laneve, A. Rosato, M. Panella
Efficient Edge AI
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Finite precision implementation of random vector functional-link networks
November 7, 2017
Optimized RVFL neural networks enable accurate AI on low-power hardware using finite precision and genetic algorithms.
A. Rosato, R. Altilio, M. Panella
Efficient Edge AI
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A nonuniform quantizer for hardware implementation of neural networks
November 2, 2017
Nonuniform quantization and genetic algorithms optimize neural networks for efficient implementation on low-precision hardware.
R. Altilio, A. Rosato, M. Panella
Distributed Learning
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Distributed Learning of Random Weights Fuzzy Neural Networks
November 10, 2016
Self-organizing distributed AI systems enable scalable, resilient learning across networks without centralized control.
R. Fierimonte, M. Barbato, A. Rosato, M. Panella
Renewable energy
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Embedding of time series for the prediction in photovoltaic power plants
September 1, 2016
AI models forecast solar power output with high accuracy using time series embedding from real photovoltaic plant data.
A. Rosato, R. Altilio, R. Araneo, M. Panella
Distributed Learning
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Recent Advances on Distributed Unsupervised Learning
June 19, 2016
Distributed clustering enables intelligent, resilient data analysis across sensor networks without centralized supervision.
A. Rosato, R. Altilio, M. Panella

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VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
GRID+ Copyright © 2026. All Rights Reserved.
VAT No. 17387741006 | The capital has been paid up in full €10,000 | RM – 1715269
P. IVA 17387741006 · The capital has been paid up in full €10,000 | RM – 1715269
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