Phone (office): +39 049 827 7774
Biography
Matteo Caligiuri is a Ph.D. Student in Computer Vision and Computer Graphics at the Department of Information Engineering of the University of Padova.
He received his Bachelor’s Degree in Information Engineering in 2020 and his Master’s Degree in ICT for Internet and Multimedia Engineering (with honors) from the University of Padova in 2022.
In 2022 he spent 6 months at Sony Europe in Stuttgart, Germany, as a master’s thesis student.
Research areas
Federated Learning
Federated learning is a decentralized machine learning approach that allows multiple devices to collaboratively train a shared model while keeping their local data private.
Multi-Modal Learning
Multimodal learning is an area of machine learning that deals with the integration and analysis of information from multiple modalities, such as text, images, audio, and video.
Time-Of-Flight sensors
Denoising and Multi-Path Interference (MPI) removal techniques for Time-of-Flight (ToF) sensors, stereo and ToF data fusion.
Publications
2025
When Cars meet Drones: Hyperbolic Federated Learning for Source-Free Domain Adaptation in Adverse Weather Proceedings Article
In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
2023
SynDrone-Multi-Modal UAV Dataset for Urban Scenarios Proceedings Article
In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 2210–2220, 2023.
2022
A Bayesian Game of Multisource Energy Harvesting for Batteryless IoT Devices Proceedings Article
In: 2022 International Conference on Electrical and Information Technology (IEIT), pp. 414–419, IEEE 2022.
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Non-Line-of-Sight Imaging from iToF data Journal Article
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