Assistant Professor (RTDA) in the Department of Informatics, Systems and Communication (DISCo) at the University of Milano-Bicocca, and researcher at the Intelligent Sensing Laboratory (ISLab). His research interests include machine learning applied to digital signal processing, computational imaging, remote sensing and biomedical signals analysis.
He obtained his Bachelor’s and Master’s degrees in Computer Science at the University of Milano-Bicocca (Italy) in 2015 and 2018 respectively, focusing on image processing and enhancement. In 2018, he worked at the NEC Corporation in Tokyo, Japan, as a research intern on image denoising and enhancement, and obtained a research grant at the Imaging and Vision Laboratory of the University of Milano-Bicocca. He obtained his PhD in 2022 at the University of Milano-Bicocca (Italy), where he is currently employed as an Assistant Professor, having spent two years as a postdoctoral researcher at the National Institute of Nuclear Physics (INFN). He is currently working on the AdvaNced Technologies for Human-centred Medicine (ANTHEM) project.
He is an Associate Editor for Neurocomputing (Elsevier) and Frontiers in Artificial Intelligence, and has also served as a Topic Editor and Guest Editor for the MDPI Journal of Imaging. He is also a member of the IEEE CTSoc Machine Learning, Deep Learning and AI in CE (MDA) Technical Committee.
Journal Articles
Proceedings
2026 Alzheimer's disease classification from EEG using a multiscale temporal deep network Zini, S., Barbera, T., Bianco, S., Napoletano, P. (2026). Alzheimer's disease classification from EEG using a multiscale temporal deep network. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 114(1 April 2026) [10.1016/j.bspc.2025.109321].2025 Bayesian nights: Optimizing night photography rendering with Bayesian derivative-free methods Zini, S., Buzzelli, M. (2025). Bayesian nights: Optimizing night photography rendering with Bayesian derivative-free methods. PATTERN RECOGNITION, 161(May 2025) [10.1016/j.patcog.2024.111314].2025 On Using AI for EEG-Based BCI Applications: Problems, Current Challenges and Future Trends Barbera, T., Burger, J., D'Amelio, A., Zini, S., Bianco, S., Lanzarotti, R., et al. (2025). On Using AI for EEG-Based BCI Applications: Problems, Current Challenges and Future Trends. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION [10.1080/10447318.2025.2561185].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 Analysis of biases in automatic white balance datasets and methods Buzzelli, M., Zini, S., Bianco, S., Ciocca, G., Schettini, R., Tchobanou, M. (2023). Analysis of biases in automatic white balance datasets and methods. COLOR RESEARCH AND APPLICATION, 48(1 (January/February 2023)), 40-62 [10.1002/col.22822].2022 Laplacian encoder-decoder network for raindrop removal Zini, S., Buzzelli, M. (2022). Laplacian encoder-decoder network for raindrop removal. PATTERN RECOGNITION LETTERS, 158, 24-33 [10.1016/j.patrec.2022.04.016].2022 COCOA: Combining Color Constancy Algorithms for Images and Videos Zini, S., Buzzelli, M., Bianco, S., Schettini, R. (2022). COCOA: Combining Color Constancy Algorithms for Images and Videos. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 8, 795-807 [10.1109/TCI.2022.3203889].2020 Deep Residual Autoencoder for Blind Universal JPEG Restoration Zini, S., Bianco, S., Schettini, R. (2020). Deep Residual Autoencoder for Blind Universal JPEG Restoration. IEEE ACCESS, 8, 63283-63294 [10.1109/ACCESS.2020.2984387].
2026 Decoding Affective States from fMRI Using Automatically Labeled Multi-modal Movie Stimuli Corsico, A., Rigamonti, G., Zini, S., Celona, L., Napoletano, P. (2026). Decoding Affective States from fMRI Using Automatically Labeled Multi-modal Movie Stimuli. In Image Analysis and Processing - ICIAP 2025 Workshops 23rd International Conference, Rome, Italy, September 15–19, 2025, Proceedings, Part I (pp.89-100) [10.1007/978-3-032-11317-7_8].2024 Lightweight Graph Neural Network for Dementia Assessment from EEG Recordings Barbera, T., Zini, S., Bianco, S., Napoletano, P. (2024). Lightweight Graph Neural Network for Dementia Assessment from EEG Recordings. In 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI) (pp.190-195). Institute of Electrical and Electronics Engineers Inc. [10.1109/rtsi61910.2024.10761763].2023 Back to the future: a night photography rendering ISP without deep learning Zini, S., Rota, C., Buzzelli, M., Bianco, S., Schettini, R. (2023). Back to the future: a night photography rendering ISP without deep learning. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp.1465-1473). IEEE Computer Society [10.1109/CVPRW59228.2023.00151].2023 Shallow Camera Pipeline for Night Photography Enhancement Zini, S., Rota, C., Buzzelli, M., Bianco, S., Schettini, R. (2023). Shallow Camera Pipeline for Night Photography Enhancement. In Image Analysis and Processing – ICIAP 2023
22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I (pp.51-61). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-43148-7_5].2023 NTIRE 2023 Challenge on Night Photography Rendering Shutova, A., Ershov, E., Perevozchikov, G., Ermakov, I., Banic, N., Timofte, R., et al. (2023). NTIRE 2023 Challenge on Night Photography Rendering. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp.1982-1993). IEEE Computer Society [10.1109/CVPRW59228.2023.00192].2023 Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training Zini, S., Gomez-Villa, A., Buzzelli, M., Twardowski, B., Bagdanov, A., van de Weijer, J. (2023). Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training. In 11th International Conference on Learning Representations, ICLR 2023 (pp.1-12). International Conference on Learning Representations, ICLR [10.48550/arXiv.2202.07993].2022 NTIRE 2022 Challenge on Night Photography Rendering Ershov, E., Savchik, A., Shepelev, D., Banic, N., Brown, M., Timofte, R., et al. (2022). NTIRE 2022 Challenge on Night Photography Rendering. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp.1286-1299). IEEE Computer Society [10.1109/CVPRW56347.2022.00135].2022 A Framework for Contrast Enhancement Algorithms Optimization Zini, S., Buzzelli, M., Bianco, S., Schettini, R. (2022). A Framework for Contrast Enhancement Algorithms Optimization. In Proceedings - International Conference on Image Processing, ICIP (pp.1431-1435). Piscataway, NJ : IEEE [10.1109/ICIP46576.2022.9897184].2021 On the Impact of Rain over Semantic Segmentation of Street Scenes Zini, S., Buzzelli, M. (2021). On the Impact of Rain over Semantic Segmentation of Street Scenes. In Pattern Recognition. ICPR International Workshops and Challenges
Virtual Event, January 10–15, 2021, Proceedings, Part VI (pp.597-610). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-68780-9_46].2021 Analysis of Biases in Automatic White Balance Datasets Bianco, S., Buzzelli, M., Ciocca, G., Schettini, R., Tchobanou, M., Zini, S. (2021). Analysis of Biases in Automatic White Balance Datasets. In Proceedings of the International Colour Association (AIC) Conference 2021 (pp.233-238).2020 CNN-based Rain Reduction in Street View Images Zini, S., Bianco, S., Schettini, R. (2020). CNN-based Rain Reduction in Street View Images. In London Imaging Meeting 2020: Future Colour Imaging (pp.78-81). Society for Imaging Science and Technology [10.2352/issn.2694-118X.2020.LIM-12].2019 Artifact-Free Thin Cloud Removal Using Gans Toizumi, T., Zini, S., Sagi, K., Kaneko, E., Tsukada, M., Schettini, R. (2019). Artifact-Free Thin Cloud Removal Using Gans. In Proceedings - International Conference on Image Processing, ICIP (pp.3596-3600). IEEE Computer Society [10.1109/ICIP.2019.8803652].2019 NTIRE 2019 challenge on real image denoising: Methods and results Abdelhamed, A., Timofte, R., Brown, M., Yu, S., Park, B., Jeong, J., et al. (2019). NTIRE 2019 challenge on real image denoising: Methods and results. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp.2197-2210). IEEE Computer Society [10.1109/CVPRW.2019.00273].