Dottorato in Ingegneria Informatica E Dei Sistemi , 37o ciclo (2021-2024)
Dottorato concluso nel 2025
Tesi:
Theory-guided Data Science models (Abstract)
Tutori:
Daniele Apiletti
Presentazione della ricerca:
PosterProfilo
Argomento di ricerca
theory-based machine learning strategies, graph neural networks, machine learning
Interessi di ricerca
Biografia
Simone is a PhD student at the Department of Control and Computer Engineering. He obtained the Master’s degree jointly at Politecnico di Torino and Université Paris-Saclay (Paris Sud) on Physics of Complex Systems. He is currently working on Graph and Convolutional neural network applications to different domains. His research interest relates to theory-based machine learning strategies, i.e. the integration of data-agnostic prior knowledge to deep learning models to enhance their predictions.
Settore scientifico discliplinare
(Area 0009 - Ingegneria industriale e dell'informazione)
Premi e riconoscimenti
- Inizio di attività di ricerca su invito presso il Computer Lab dell'Università di Cambridge, sotto la guida del Prof. Pietro Liò. (2024)
- Information required for participating to the PhD Quality Awards (2024)
- Invited Talk in the cycle Foundation AI, under the invitation of Prof. Pietro Liò, with the title "Enhancing Climate Prediction with Knowledge Infused Deep Learning Models" https://talks.cam.ac.uk/talk/index/222046 (2024)
Didattica
Collegi dei Corsi di Studio
- Collegio di Ingegneria Gestionale e della Produzione. Componente invitato
- Collegio di Ingegneria Informatica, del Cinema e Meccatronica. Componente invitato
Insegnamenti
Corso di laurea magistrale
- Challenge@PoliTo by Firms - Enertech. A.A. 2022/23, INGEGNERIA GESTIONALE (ENGINEERING AND MANAGEMENT). Collaboratore del corso
- Challenge@PoliTo by Students PoliTO - Living with natural risks. A.A. 2023/24, INGEGNERIA GESTIONALE (ENGINEERING AND MANAGEMENT). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2022/23, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Business intelligence per big data. A.A. 2024/25, INGEGNERIA GESTIONALE. Collaboratore del corso
- Distributed architectures for big data processing and analytics. A.A. 2024/25, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Data management and visualization. A.A. 2021/22, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Data management and visualization. A.A. 2022/23, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Data management and visualization. A.A. 2023/24, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Data management and visualization. A.A. 2024/25, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
Corso di laurea di 1° livello
- Introduction to databases. A.A. 2021/22, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
Ricerca
Gruppi di ricerca
Dottorandi
- Marco De Luca. Corso in Ingegneria Informatica E Dei Sistemi (ciclo 41, 2025-in corso)
Data science, Computer vision and AI Data science, Computer vision and AI Data science, Computer vision and AI
Pubblicazioni
Coautori PoliTO
Pubblicazioni durante il dottorato Vedi tutte le pubblicazioni su Porto@Iris
- Monaco, Simone; Monaco, Luca; Apiletti, Daniele; Cremonini, Roberto; Barbero, Secondo (2025)
Uncertainty-aware methods for enhancing rainfall prediction with deep-learning based post-processing segmentation. In: COMPUTERS & GEOSCIENCES, vol. 205. ISSN 0098-3004
Contributo su Rivista - Monaco, Simone (2025)
Theory-guided Data Science models. relatore: APILETTI, DANIELE; , 37. XXXVII Ciclo, P.: 125
Doctoral Thesis - Vazirov, Etibar; Monaco, Simone; Apiletti, Daniele (2025)
Prediction of coffee consumption using Graph Neural Networks and Explainable AI. In: 19th IEEE International Conference on Application of Information and Communication Technologies (AICT), Al-Ain (UAE), 29-31 October 2025. ISBN: 979-8-3315-9342-1
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Apiletti, Daniele; Francica, Andrea; Cerquitelli, Tania (2025)
Quantify production planning efficiency through predictive modeling in manufacturing systems. In: COMPUTERS & INDUSTRIAL ENGINEERING, vol. 201. ISSN 0360-8352
Contributo su Rivista - Celia, Matteo; Monaco, Simone; Apiletti, Daniele (2025)
A Comparative Study of Neural Ordinary Differential Equations and Neural Operators for Modeling Temporal Dynamics. In: NEURAL COMPUTING & APPLICATIONS, vol. 37, pp. 25319-25338. ISSN 1433-3058
Contributo su Rivista - Monaco, Simone; Bussola, Nicole; Buttò, Sara; Sona, Diego; Giobergia, Flavio; Jurman, ... (2024)
AI models for automated segmentation of engineered polycystic kidney tubules. In: SCIENTIFIC REPORTS, vol. 14. ISSN 2045-2322
Contributo su Rivista - Fassio, Simone; Monaco, Simone; Apiletti, Daniele (2024)
Deep Probability Segmentation: Are segmentation models probability estimators?. In: The 18th IEEE International Conference on Application of Information and Communication Technologies (AICT), Torino (ITA), 25-27 September 2024. ISBN: 979-8-3503-8753-7
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Monaco, Luca; Apiletti, Daniele (2024)
Uncertainty-aware segmentation for rainfall prediction post processing. In: 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Workshops, Barcellona, August 25, 2024 - August 29, 2024
Contributo in Atti di Convegno (Proceeding) - Koudounas, Alkis; Giobergia, Flavio; Benedetto, Irene; Monaco, Simone; Cagliero, Luca; ... (2023)
baρtti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy. In: EVALITA 2023, Parma (ITA), September 7th - 8th, 2023. ISSN 1613-0073
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Apiletti, Daniele (2023)
Training physics-informed neural networks: One learning to rule them all?. In: RESULTS IN ENGINEERING, vol. 18. ISSN 2590-1230
Contributo su Rivista - Monaco, Simone; Barresi, Sebastiano; Apiletti, Daniele (2023)
Lorentz-invariant augmentation for high-energy physics. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Turin (ITA), September 18-22 2023. ISSN 1865-0937
Contributo in Atti di Convegno (Proceeding) - Colomba, Luca; Farasin, Alessandro; Monaco, Simone; Greco, Salvatore; Garza, Paolo; ... (2022)
A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. In: International Conference on Information and Knowledge Management (CIKM) 2022, Atlanta (Georgia, USA), 17/10/2022 - 21/10/2022, pp. 3893-3897. ISBN: 978-1-4503-9236-5
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Apiletti, Daniele (2022)
Experimental Comparison of Theory-Guided Deep Learning Algorithms. In: European Conference on Advances in Databases and Information Systems (ADBIS 2022), Torino, September 5-8 2022, pp. 256-265. ISSN 1865-0929. ISBN: 978-3-031-15742-4
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Apiletti, Daniele; Malnati, Giovanni (2022)
Theory-Guided Deep Learning Algorithms: An Experimental Evaluation. In: ELECTRONICS, vol. 11. ISSN 2079-9292
Contributo su Rivista - Monaco, Simone; Bethaz, Paolo; Apiletti, Daniele; Baldini, Fabrizio Pio; Caso, Carlo; ... (2022)
Exploring waste-collection fleet data: challenges in a real-world use case from multiple data providers. In: EDBT/ICDT Workshop, 6th International workshop on Data Analytics solutions for Real-LIfe APplications, Edinburgh, March 29 - April 1, 2022
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Farasin, Alessandro; ... (2021)
Double-Step deep learning framework to improve wildfire severity classification. In: Workshops of the 24th International Conference on Extending Database Technology/24th International Conference on Database Theory, EDBT-ICDT 2021, Nicosia (Cyprus), March 23-26, 2021. ISBN: 978-3-89318-084-4
Contributo in Atti di Convegno (Proceeding) - Monaco, Simone; Greco, Salvatore; Farasin, Alessandro; Colomba, Luca; Apiletti, Daniele; ... (2021)
Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction. In: APPLIED SCIENCES, vol. 11. ISSN 2076-3417
Contributo su Rivista - Marguglio, Angelo; Veneziano, Giuseppe; Greco, Pietro; Jung, Sven; Siegburg, Robert; ... (2021)
A hybrid cloud-to-edge predictive maintenance platform. In: Predictive Maintenance in Smart Factories / Marguglio A., Veneziano G., Greco P., Jung S., Siegburg R., Schmitt R. H., Monaco S., Apiletti D., Cerquitelli T., Nikolakis N., Macii E., S.L., Springer, pp. 19-37. ISBN: 978-981-16-2939-6
Contributo in Volume - Monaco, Simone; Bussola, Nicole; Butto, Sara; Sona, Diego; Apiletti, Daniele; Jurman, ... (2021)
Cyst segmentation on kidney tubules by means of U-Net deep-learning models. In: IEEE International Conference on Big Data, 15-18 Dec. 2021, pp. 3923-3926. ISBN: 978-1-6654-3902-2
Contributo in Atti di Convegno (Proceeding)