Luca Romeo

@docenti.unimc.it

Tenure Track Assistant Professor Computer Science, at Department Economics and Law
University of Macerata

Luca Romeo


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https://researchid.co/lucaromeo89
LUCA ROMEO received a Ph.D. degree in computer science from the Department of Information Engineering (DII), Università Politecnica delle Marche, in 2018. His Ph.D. thesis was on "applied machine learning for human motion analysis and affective computing". He is currently a Tenure Track Assistant Professor of Computer Science with University of Macerata | UniMC Department Economics and Law. He is also Adjunct Professor of Customer Intelligence & Big Data, at Luiss, Roma and he is affiliated with the Unit of Computational Statistics and Machine Learning, Fondazione Istituto Italiano di Tecnologia Genova. His research topics include the design of novel Machine learning algorithms for solving relevant challenges in different real-world domains.

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence
92

Scopus Publications

4070

Scholar Citations

33

Scholar h-index

57

Scholar i10-index

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

  • A novel multi-task multi-view approach with custom multi-label loss for fault detection in complex industrial apparatus
    R Rosati, L Pepa, L Romeo
    Advanced Engineering Informatics 73, 104592 , 2026
    2026
  • Ordinal evolutionary artificial neural networks for predicting diabetic nephropathy progression
    AM Gómez-Orellana, M Bernardini, R Ayllón-Gavilán, VM Vargas, ...
    Applied Soft Computing, 115153 , 2026
    2026
  • Machine Learning-Based Clinical Decision Support System for Hepatic Fibrosis Risk Prediction in General Practice
    M Bernardini, M di Cosmo, G Barone, L Romeo, E Frontoni
    ACM Transactions on Computing for Healthcare , 2026
    2026
  • Type 2 Diabetes Prediction from Multi-center Electronic Health Records in General Practice Using Machine Learning
    M Rerisi, M Di Cosmo, M Bernardini, L Romeo
    International Workshop on Artificial Intelligence for Biomedical Data, 39-46 , 2025
    2025
  • A machine learning algorithm for the prediction of complications incorporated in electronic medical records improves type 2 diabetes care
    A Nicolucci, G Vespasiani, D Mannino, GT Russo, G Lucisano, MC Rossi, ...
    Diabetes Research and Clinical Practice, 112900 , 2025
    2025
    Citations: 2
  • ML-predicted surgical site infections: An epidemiological study utilizing machine learning on routinely collected healthcare data to predict infection risk
    D Golinelli, S Rosa, P Rucci, F Sanmarchi, D Tedesco, C Biagetti, A Gili, ...
    Smart Health 37, 100596 , 2025
    2025
    Citations: 5
  • Knee Osteoarthritis Severity Grading Using Soft Labelling and Ordinal Classification
    F Bérchez-Moreno, VM Vargas, AM Gómez-Orellana, D Guijo-Rubio, ...
    International Work-Conference on Artificial Neural Networks, 522-533 , 2025
    2025
    Citations: 1
  • Single-and multi-task linear models for ATMs fault classification in human-centered predictive maintenance
    R Rosati, L Romeo, A Mancini
    Computers & Industrial Engineering 200, 110763 , 2025
    2025
    Citations: 5
  • ArtifiAI for Aging Rehabilitation and Intelligent Assisted Living
    SS Khan, L Romeo, A Abedi
    2025
  • Corrections to “On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security”
    O Kuznetsov, P Sernani, L Romeo, E Frontoni, A Mancini
    IEEE Access 12, 162550-162550 , 2024
    2024
  • Neighborhood Component Feature Selection for Multiple Instance Learning Paradigm
    G Turri, L Romeo
    Joint European Conference on Machine Learning and Knowledge Discovery in … , 2024
    2024
  • Algor-ethics: charting the ethical path for AI in critical care
    J Montomoli, MM Bitondo, M Cascella, E Rezoagli, L Romeo, V Bellini, ...
    Journal of clinical monitoring and computing 38 (4), 931-939 , 2024
    2024
    Citations: 49
  • Enhancing copy-move forgery detection through a novel CNN architecture and comprehensive dataset analysis
    O Kuznetsov, E Frontoni, L Romeo, R Rosati
    Multimedia Tools and Applications 83 (21), 59783-59817 , 2024
    2024
    Citations: 29
  • Image steganalysis using deep learning models
    A Kuznetsov, N Luhanko, E Frontoni, L Romeo, R Rosati
    Multimedia Tools and Applications 83 (16), 48607-48630 , 2024
    2024
    Citations: 22
  • Learning Ordinal–Hierarchical Constraints for Deep Learning Classifiers
    R Rosati, L Romeo, VM Vargas, PA Gutiérrez, E Frontoni, ...
    IEEE Transactions on Neural Networks and Learning Systems , 2024
    2024
    Citations: 5
  • On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security (vol 12, pg 3881, 2024)
    O Kuznetsov, P Sernani, L Romeo, E Frontoni, A Mancini
    IEEE ACCESS 12, 162550-162550 , 2024
    2024
  • CAlibrazione e SImulazione di un modello macroECOnomico di grandi dimensioni (CASIECO)
    L Riccetti, L Romeo
    2024
  • METODO PER LA PREDIZIONE DELL'INSORGENZA DI COMPLICANZE A BREVE-MEDIO TERMINE NEL PAZIENTE DIABETICO E DELLA LORO STRATIFICAZIONE TEMPORALE
    G Vespasiani, M Vespasiani, E Frontoni, L Romeo, M Bernardini, ...
    2024
  • Mitigating Bias in Aesthetic Quality Control Tasks: An Adversarial Learning Approach
    D Bernovschi, A Giacomini, R Rosati, L Romeo
    Procedia Computer Science 232, 719-725 , 2024
    2024
    Citations: 2
  • Data augmentation strategy for generating realistic samples on defect segmentation task
    M Martini, R Rosati, L Romeo, A Mancini
    Procedia Computer Science 232, 1597-1606 , 2024
    2024
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • Machine Learning approach for Predictive Maintenance in Industry 4.0
    M Paolanti, L Romeo, A Felicetti, A Mancini, E Frontoni, J Loncarski
    2018 14th IEEE/ASME International Conference on Mechatronic and Embedded … , 2018
    2018
    Citations: 403
  • From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
    R Rosati, L Romeo, G Cecchini, F Tonetto, P Viti, A Mancini, E Frontoni
    Journal of Intelligent Manufacturing 34 (1), 107-121 , 2023
    2023
    Citations: 332
  • A sequential deep learning application for recognising human activities in smart homes
    D Liciotti, M Bernardini, L Romeo, E Frontoni
    Neurocomputing 396, 501-513 , 2020
    2020
    Citations: 253
  • The KIMORE Dataset: KInematic Assessment of MOvement and Clinical Scores for Remote Monitoring of Physical REhabilitation
    M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, A Monteriù, L Romeo, ...
    IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (7 … , 2019
    2019
    Citations: 206
  • On the integration of artificial intelligence and blockchain technology: a perspective about security
    O Kuznetsov, P Sernani, L Romeo, E Frontoni, A Mancini
    IEEE Access 12, 3881-3897 , 2024
    2024
    Citations: 191
  • SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0
    M Calabrese, M Cimmino, F Fiume, M Manfrin, L Romeo, S Ceccacci, ...
    Information 11 (4), 202 , 2020
    2020
    Citations: 191
  • Harnessing the power of smart and connected health to tackle covid-19: Iot, ai, robotics, and blockchain for a better world
    F Firouzi, B Farahani, M Daneshmand, K Grise, J Song, R Saracco, ...
    IEEE Internet of Things Journal 8 (16), 12826-12846 , 2021
    2021
    Citations: 176
  • Discovering the type 2 diabetes in electronic health records using the sparse balanced support vector machine
    M Bernardini, L Romeo, P Misericordia, E Frontoni
    IEEE Journal of Biomedical and Health Informatics 24 (1), 235-246 , 2019
    2019
    Citations: 152
  • Real-time mental stress detection based on smartwatch
    L Ciabattoni, F Ferracuti, S Longhi, L Pepa, L Romeo, F Verdini
    2017 IEEE International Conference on Consumer Electronics (ICCE), 110-111 , 2017
    2017
    Citations: 148
  • Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0
    L Romeo, J Loncarski, M Paolanti, G Bocchini, A Mancini, E Frontoni
    Expert Systems with Applications 140, 112869 , 2020
    2020
    Citations: 121
  • A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment
    M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, V Kyrki, A Monteriu, ...
    Journal of biomedical informatics 78, 1-11 , 2018
    2018
    Citations: 98
  • Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients
    J Montomoli, L Romeo, S Moccia, M Bernardini, L Migliorelli, D Berardini, ...
    Journal of Intensive Medicine 1 (02), 110-116 , 2021
    2021
    Citations: 97
  • A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation
    A Monteriù, M Prist, E Frontoni, S Longhi, F Pietroni, S Casaccia, ...
    Sensors 18 (7), 2310 , 2018
    2018
    Citations: 89
  • Prediction of complications of type 2 Diabetes: A Machine learning approach
    A Nicolucci, L Romeo, M Bernardini, M Vespasiani, MC Rossi, M Petrelli, ...
    Diabetes Research and Clinical Practice 190, 110013 , 2022
    2022
    Citations: 73
  • Accuracy evaluation of the kinect v2 sensor during dynamic movements in a rehabilitation scenario
    M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, S Longhi, L Romeo, ...
    2016 38th Annual International Conference of the IEEE Engineering in … , 2016
    2016
    Citations: 72
  • Multiple instance learning for emotion recognition using physiological signals
    L Romeo, A Cavallo, L Pepa, N Bianchi-Berthouze, M Pontil
    IEEE Transactions on Affective Computing 13 (1), 389-407 , 2019
    2019
    Citations: 68
  • Robotic retail surveying by deep learning visual and textual data
    M Paolanti, L Romeo, M Martini, A Mancini, E Frontoni, P Zingaretti
    Robotics and Autonomous Systems 118, 179-188 , 2019
    2019
    Citations: 65
  • Faster R-CNN approach for detection and quantification of DNA damage in comet assay images
    R Rosati, L Romeo, S Silvestri, F Marcheggiani, L Tiano, E Frontoni
    Computers in Biology and Medicine 123, 103912 , 2020
    2020
    Citations: 62
  • Early temporal prediction of type 2 diabetes risk condition from a general practitioner electronic health record: A multiple instance boosting approach
    M Bernardini, M Morettini, L Romeo, E Frontoni, L Burattini
    Artificial Intelligence in Medicine 105, 101847 , 2020
    2020
    Citations: 61
  • Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke
    P Sale, G Ferriero, L Ciabattoni, AM Cortese, F Ferracuti, L Romeo, ...
    Journal of Stroke and Cerebrovascular Diseases 27 (11), 2962-2972 , 2018
    2018
    Citations: 52