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|cellpadding="100" width="100%" align="right" style="color:#337ab7; font-size: 18pt; font-weight: bold;"|Walter Brescia | |cellpadding="100" width="100%" align="right" style="color:#337ab7; font-size: 18pt; font-weight: bold;"|Walter Brescia | ||
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| − | |width="85%" align="right" valign="middle" style="color:yellow; background:#283d78; font-weight:bold;"| Eng, PhD | + | |width="85%" align="right" valign="middle" style="color:yellow; background:#283d78; font-weight:bold;"| Eng, PhD, Researcher |
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{{Panel|icon=graduation-cap|title=Publications|body= | {{Panel|icon=graduation-cap|title=Publications|body= | ||
| + | ==2025== | ||
| + | <paper authors="N. Barone, W. Brescia, G. Santangelo, A. Maggio, I. Cisternino, L. De Cicco, S. Mascolo" conference="ACM Multimedia Systems (MMSys) - Best Demo Paper" place="Stellenbosch, South Africa" date="March-April 2025" pdf="mmsys2025.pdf"> | ||
| + | Real-time Point Cloud Transmission for Immersive Teleoperation of Autonomous Mobile Robots | ||
| + | </paper> | ||
| − | + | ==2024== | |
<paper authors="Nunzio Barone, Walter Brescia, Saverio Mascolo, Luca De Cicco" conference="Proc. of ACM MMSys 2024" place="Bari, Italy" date="15-18 April 2024" pdf="apeiron2.pdf"> | <paper authors="Nunzio Barone, Walter Brescia, Saverio Mascolo, Luca De Cicco" conference="Proc. of ACM MMSys 2024" place="Bari, Italy" date="15-18 April 2024" pdf="apeiron2.pdf"> | ||
APEIRON: a Multimodal Drone Dataset Bridging Perception and Network Data in Outdoor Environments | APEIRON: a Multimodal Drone Dataset Bridging Perception and Network Data in Outdoor Environments | ||
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Walter Brescia |
| Eng, PhD, Researcher |
Walter Brescia graduated cum laude in Computer Engineering from Politecnico di Bari in December 2020, with a thesis titled "A Deep Reinforcement Learning Approach for Autonomous Mobile Robots".
His research spans multiple areas, including control strategies for industrial autonomous vehicles, reinforcement learning and machine learning for robotics. He has presented his works at international conferences such as IFAC WC 2023, IEEE MED 2023, and ACM MMSys.
Walter Brescia is a member of the Control Engineering and Computer Science Laboratory (C3Lab) at Politecnico di Bari, where he collaborates on projects related to reinforcement learning and robotics.|
|
Walter Brescia |
| Eng, PhD Student |
Walter Brescia graduated cum laude in Computer Engineering from Politecnico di Bari in December 2020, with a thesis titled "A Deep Reinforcement Learning Approach for Autonomous Mobile Robots".
His research spans multiple areas, including control strategies for industrial autonomous vehicles, reinforcement learning and machine learning for robotics. He has presented his works at international conferences such as IFAC WC 2023, IEEE MED 2023, and ACM MMSys.
Walter Brescia is a member of the Control Engineering and Computer Science Laboratory (C3Lab) at Politecnico di Bari, where he collaborates on projects related to reinforcement learning and robotics.