Matteo Caligiuri | Ph.D. Student

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

2023

Rizzoli, Giulia; Barbato, Francesco; Caligiuri, Matteo; Zanuttigh, Pietro

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.

BibTeX

2022

Caligiuri, Matteo; Galizio, Daniele; Lincetto, Federico; Gindullina, Elvina; Badia, Leonardo

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.

BibTeX

0000

Caligiuri, Matteo

Non-Line-of-Sight Imaging from iToF data Journal Article

In: 0000.

BibTeX