BORGHESI, ANDREA
BORGHESI, ANDREA
DISI - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA
Docenti di ruolo di IIa fascia
An online algorithm for power consumption prediction of HPC workload
2026 Antici, F.; Borghesi, A.; Kiziltan, Z.; Domke, J.; Bartolini, A.
Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images
2025 Bellatreccia, C.; Zama, D.; Dondi, A.; Pierantoni, L.; Laura, A.; Neri, I.; Lanari, M.; Borghesi, A.; Calegari, R.
AI-fairness: the FAIRBRIDGE approach to practically bridge the gap between socio-legal and technical perspectives
2025 Ciatto, G.; Matteini, M.; Sartori, L.; Rebrean, M.; Muller, C.; Borghesi, A.; Calegari, R.
C6EnPLS: A High-Performance Computing Job Dataset for the Analysis of Linear Solvers’ Power Consumption
2025 Artioli, Marcello; Borghesi, Andrea; Chinnici, Marta; Ciampolini, Anna; Colonna, Michele; De Chiara, Davide; Loreti, Daniela
UoPC: A User-Based Online Framework to Predict Job Power Consumption in HPC Systems
2025 Antici, F; Borghesi, A; Domke, J; Kiziltan, Z
Generation of Clinical Skin Images with Pathology with Scarce Data
2024 Borghesi, Andrea; Calegari, Roberta
GRAAFE: GRaph anomaly anticipation framework for exascale HPC systems
2024 Molan, M.; Seyedkazemi Ardebili, Mohsen; Khan, J. A.; Beneventi, F.; Cesarini, D.; Borghesi, A.; Bartolini, A.
Harnessing federated learning for anomaly detection in supercomputer nodes
2024 Farooq, Emmen; Milano, Michela; Borghesi, Andrea
LSTM-Based Unsupervised Anomaly Detection in High-Performance Computing: A Federated Learning Approach
2024 Farooq, Emmen; Borghesi, Andrea
Machine learning approaches to predict the execution time of the meteorological simulation software COSMO
2024 De Filippo A.; Di Giacomo E.; Borghesi A.
Online Job Failure Prediction in an HPC System
2024 Antici, F.; Borghesi, A.; Kiziltan, Z.
Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology
2024 Zama, D.; Borghesi, A.; Ranieri, A.; Manieri, E.; Pierantoni, L.; Andreozzi, L.; Dondi, A.; Neri, I.; Lanari, M.; Calegari, R.
A Federated Learning Approach for Anomaly Detection in High Performance Computing
2023 Farooq, Emmen; Borghesi, Andrea
ExaMon-X: a Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems
2023 Borghesi, Andrea; Burrello, Alessio; Bartolini, Andrea
Graph Neural Networks for Anomaly Anticipation in HPC Systems
2023 Molan M.; Ahmed Khan J.; Borghesi A.; Bartolini A.
M100 ExaData: a data collection campaign on the CINECA's Marconi100 Tier-0 supercomputer
2023 Borghesi, Andrea; Di Santi, Carmine; Molan, Martin; Ardebili, Mohsen Seyedkazemi; Mauri, Alessio; Guarrasi, Massimiliano; Galetti, Daniela; Cestari, Mirko; Barchi, Francesco; Benini, Luca; Beneventi, Francesco; Bartolini, Andrea
Machine Learning Methodologies to Support HPC Systems Operations: Anomaly Detection
2023 Molan M.; Borghesi A.; Benini L.; Bartolini A.
Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product
2023 Molan, G; Dolinar, G; Bojkovski, J; Prodan, R; Borghesi, A; Molan, M
MusiComb: a Sample-based Approach to Music Generation Through Constraints
2023 Giuliani, Luca; Ballerini, Francesco; De Filippo, Allegra; Borghesi, Andrea
RUAD: Unsupervised anomaly detection in HPC systems
2023 Molan, M.; Borghesi, A.; Cesarini, D.; Benini, L.; Bartolini, A.
| Titolo | Autore(i) | Anno | Periodico | Editore | Tipo | File |
|---|---|---|---|---|---|---|
| An online algorithm for power consumption prediction of HPC workload | Antici, F.; Borghesi, A.; Kiziltan, Z.; Domke, J.; Bartolini, A. | 2026-01-01 | FUTURE GENERATION COMPUTER SYSTEMS | - | 1.01 Articolo in rivista | 1-s2.0-S0167739X25003590-main.pdf |
| Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images | Bellatreccia, C.; Zama, D.; Dondi, A.; Pierantoni, L.; Laura, A.; Neri, I.; Lanari, M.; Borghesi,... A.; Calegari, R. | 2025-01-01 | - | CEUR-WS | 4.01 Contributo in Atti di convegno | paper8.pdf |
| AI-fairness: the FAIRBRIDGE approach to practically bridge the gap between socio-legal and technical perspectives | Ciatto, G.; Matteini, M.; Sartori, L.; Rebrean, M.; Muller, C.; Borghesi, A.; Calegari, R. | 2025-01-01 | - | IEEE Computer Society | 4.01 Contributo in Atti di convegno | 0635.pdf |
| C6EnPLS: A High-Performance Computing Job Dataset for the Analysis of Linear Solvers’ Power Consumption | Artioli, Marcello; Borghesi, Andrea; Chinnici, Marta; Ciampolini, Anna; Colonna, Michele; De Chia...ra, Davide; Loreti, Daniela | 2025-01-01 | FUTURE INTERNET | - | 1.01 Articolo in rivista | futureinternet-17-00203.pdf |
| UoPC: A User-Based Online Framework to Predict Job Power Consumption in HPC Systems | Antici, F; Borghesi, A; Domke, J; Kiziltan, Z | 2025-01-01 | - | - | 4.01 Contributo in Atti di convegno | - |
| Generation of Clinical Skin Images with Pathology with Scarce Data | Borghesi, Andrea; Calegari, Roberta | 2024-01-01 | - | - | 4.01 Contributo in Atti di convegno | preEditoriale.pdf |
| GRAAFE: GRaph anomaly anticipation framework for exascale HPC systems | Molan, M.; Seyedkazemi Ardebili, Mohsen; Khan, J. A.; Beneventi, F.; Cesarini, D.; Borghesi, A.; ...Bartolini, A. | 2024-01-01 | FUTURE GENERATION COMPUTER SYSTEMS | - | 1.01 Articolo in rivista | GRAAFE.pdf |
| Harnessing federated learning for anomaly detection in supercomputer nodes | Farooq, Emmen; Milano, Michela; Borghesi, Andrea | 2024-01-01 | FUTURE GENERATION COMPUTER SYSTEMS | - | 1.01 Articolo in rivista | FGCS_FL_Revision__2.pdf |
| LSTM-Based Unsupervised Anomaly Detection in High-Performance Computing: A Federated Learning Approach | Farooq, Emmen; Borghesi, Andrea | 2024-01-01 | - | - | 4.01 Contributo in Atti di convegno | FL_LSTM.pdf |
| Machine learning approaches to predict the execution time of the meteorological simulation software COSMO | De Filippo A.; Di Giacomo E.; Borghesi A. | 2024-01-01 | JOURNAL OF INTELLIGENT INFORMATION SYSTEMS | - | 1.01 Articolo in rivista | - |
| Online Job Failure Prediction in an HPC System | Antici, F.; Borghesi, A.; Kiziltan, Z. | 2024-01-01 | - | Springer Science and Business Media Deutschland GmbH | 4.01 Contributo in Atti di convegno | - |
| Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology | Zama, D.; Borghesi, A.; Ranieri, A.; Manieri, E.; Pierantoni, L.; Andreozzi, L.; Dondi, A.; Neri,... I.; Lanari, M.; Calegari, R. | 2024-01-01 | CHILDREN | - | 1.01 Articolo in rivista | children-11-01401.pdf |
| A Federated Learning Approach for Anomaly Detection in High Performance Computing | Farooq, Emmen; Borghesi, Andrea | 2023-01-01 | - | IEEE | 4.01 Contributo in Atti di convegno | FL_for_HPC_2.pdf |
| ExaMon-X: a Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems | Borghesi, Andrea; Burrello, Alessio; Bartolini, Andrea | 2023-01-01 | IEEE INTERNET OF THINGS JOURNAL | - | 1.01 Articolo in rivista | postPrintVersion_plus_editorialReference.pdf |
| Graph Neural Networks for Anomaly Anticipation in HPC Systems | Molan M.; Ahmed Khan J.; Borghesi A.; Bartolini A. | 2023-01-01 | - | - | 4.01 Contributo in Atti di convegno | - |
| M100 ExaData: a data collection campaign on the CINECA's Marconi100 Tier-0 supercomputer | Borghesi, Andrea; Di Santi, Carmine; Molan, Martin; Ardebili, Mohsen Seyedkazemi; Mauri, Alessio;... Guarrasi, Massimiliano; Galetti, Daniela; Cestari, Mirko; Barchi, Francesco; Benini, Luca; Beneventi, Francesco; Bartolini, Andrea | 2023-01-01 | SCIENTIFIC DATA | - | 1.01 Articolo in rivista | versione_editoriale.pdf |
| Machine Learning Methodologies to Support HPC Systems Operations: Anomaly Detection | Molan M.; Borghesi A.; Benini L.; Bartolini A. | 2023-01-01 | - | Springer | 4.01 Contributo in Atti di convegno | EUROPAR_phd_symposium_preEditoriale-1.pdf |
| Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product | Molan, G; Dolinar, G; Bojkovski, J; Prodan, R; Borghesi, A; Molan, M | 2023-01-01 | IEEE ACCESS | - | 1.01 Articolo in rivista | IEEE_Access_MOQE.pdf |
| MusiComb: a Sample-based Approach to Music Generation Through Constraints | Giuliani, Luca; Ballerini, Francesco; De Filippo, Allegra; Borghesi, Andrea | 2023-01-01 | - | IEEE | 4.01 Contributo in Atti di convegno | camReady_preEditoriale.pdf |
| RUAD: Unsupervised anomaly detection in HPC systems | Molan, M.; Borghesi, A.; Cesarini, D.; Benini, L.; Bartolini, A. | 2023-01-01 | FUTURE GENERATION COMPUTER SYSTEMS | - | 1.01 Articolo in rivista | Towards_unsupervised_anomaly_detection_in_HPC_preEditorial.pdf |