Mirko Paolo Barbato
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Mirko Paolo Barbato

Postdoctoral Fellow

DISCo (Department of Informatics, Systems and Communication)
University of Milano-Bicocca
Viale Sarca 336, Building U14, 20126 Milan, Italy
Room 1038, tel: +390264487871
e-mail: mirko.barbato@unimib.it

#Remote Sensing

#Computer Vision

#Healthcare AI Systems

He is a postdoctoral researcher in the Department of Informatics, Systems and Communication (DISCo) at the University of Milano-Bicocca in Italy and a member of the Intelligent Sensing Laboratory. His research interests lie in the application of machine learning and deep learning to computer vision and signal analysis, particularly in the context of multimodal approaches in remote sensing and healthcare systems.
He achieved his Bachelor’s degree in Computer Science at the University of Milano-Bicocca in 2017 and his Master’s degree in 2020, completing his Master’s thesis at the NEC Corporation in Tokyo. He received his PhD in Computer Science from the University of Milano-Bicocca in 2024. His doctoral research was conducted within the PIGNOLETTO project at the National Institute for Nuclear Physics (INFN) and focused on soil segmentation and classification using automatic learning techniques and multi-source data, including remote sensing and AI technologies.
He is currently working on the AdvaNced Technologies for Human-centred Medicine (ANTHEM) project, which focuses on diabetes monitoring and prediction using AI techniques.

  • Journal Articles
  • Proceedings
2025 Lightweight Sequential Transformers for Blood Glucose Level Prediction in Type-1 Diabetes Barbato, M., Rigamonti, G., Marelli, D., Napoletano, P. (2025). Lightweight Sequential Transformers for Blood Glucose Level Prediction in Type-1 Diabetes. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS [10.1109/JBHI.2025.3633194].2024 Ticino: A multi-modal remote sensing dataset for semantic segmentation Barbato, M., Piccoli, F., Napoletano, P. (2024). Ticino: A multi-modal remote sensing dataset for semantic segmentation. EXPERT SYSTEMS WITH APPLICATIONS, 249(Part A 1 September 2024) [10.1016/j.eswa.2024.123600].2024 Deep Learning Hyperspectral Pansharpening on Large-Scale PRISMA Dataset Zini, S., Barbato, M., Piccoli, F., Napoletano, P. (2024). Deep Learning Hyperspectral Pansharpening on Large-Scale PRISMA Dataset. REMOTE SENSING, 16(12) [10.3390/rs16122079].2023 Estimation of Soil Characteristics from Multispectral Sentinel-3 Imagery and DEM Derivatives Using Machine Learning Piccoli, F., Barbato, M., Peracchi, M., Napoletano, P. (2023). Estimation of Soil Characteristics from Multispectral Sentinel-3 Imagery and DEM Derivatives Using Machine Learning. SENSORS, 23(18) [10.3390/s23187876].2022 Unsupervised segmentation of hyperspectral remote sensing images with superpixels Barbato, M., Napoletano, P., Piccoli, F., Schettini, R. (2022). Unsupervised segmentation of hyperspectral remote sensing images with superpixels. REMOTE SENSING APPLICATIONS, 28 [10.1016/j.rsase.2022.100823].
2025 Multimodal Earth Observation Modeling using AI Barbato, M., Piccoli, F., Napoletano, P. (2025). Multimodal Earth Observation Modeling using AI. In Modelling and Simulation for Autonomous Systems 10th International Conference, MESAS 2023, Palermo, Italy, October 17–19, 2023, Revised Selected Papers (pp.349-363). Springer [10.1007/978-3-031-71397-2_22].2024 Multimodal Fusion Methods with Vision Transformers for Remote Sensing Semantic Segmentation Morelli, V., Barbato, M., Piccoli, F., Napoletano, P. (2024). Multimodal Fusion Methods with Vision Transformers for Remote Sensing Semantic Segmentation. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE Computer Society [10.1109/WHISPERS61460.2023.10430788].2024 Improving Detection of Type-1 Diabetes Adverse Events Using GRU Networks Rigamonti, G., Barbato, M., Marelli, D., Napoletano, P. (2024). Improving Detection of Type-1 Diabetes Adverse Events Using GRU Networks. In 8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Proceeding (pp.79-84). Institute of Electrical and Electronics Engineers Inc. [10.1109/RTSI61910.2024.10761795].