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{{Column|6|{{Panel|con=user|title=Short CV|body= | {{Column|6|{{Panel|con=user|title=Short CV|body= | ||
| − | Researcher working in the fields of control theory, robotics, and autonomous systems. He is currently a visiting postdoctoral researcher at Carleton University (Canada) and collaborates with the C3Lab at the Polytechnic University of Bari, where he received his master's degree | + | Researcher working in the fields of control theory, robotics, and autonomous systems. He is currently a visiting postdoctoral researcher at Carleton University (Canada) and collaborates with the C3Lab at the Polytechnic University of Bari, where he received his master's degree cum laude in Automation Engineering, followed by his Ph.D. in Industry 4.0 in January 2025. |
His main research interests include Model Predictive Control (MPC), Reinforcement Learning, and data-driven control methods. From an applied perspective, his work focuses on the implementation of automation algorithms on drones (UAVs), mobile robotics platforms, and video streaming systems. | His main research interests include Model Predictive Control (MPC), Reinforcement Learning, and data-driven control methods. From an applied perspective, his work focuses on the implementation of automation algorithms on drones (UAVs), mobile robotics platforms, and video streaming systems. | ||
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<paper authors="Giada Lops, Gioacchino Manfredi, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo" conference=" Workshop “Empowering Women in Science: Control Strategies to Close the Diversity and Inclusion Gap" place="Bari, Italy" date="June 2025"> | <paper authors="Giada Lops, Gioacchino Manfredi, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo" conference=" Workshop “Empowering Women in Science: Control Strategies to Close the Diversity and Inclusion Gap" place="Bari, Italy" date="June 2025"> | ||
POSTER: Safety-Aware Deep-RL for Automated Insulin Delivery: Toward Inclusive Diabetes Care | POSTER: Safety-Aware Deep-RL for Automated Insulin Delivery: Toward Inclusive Diabetes Care | ||
| + | </paper> | ||
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| + | <paper authors="Gioacchino Manfredi, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo" conference="IEEE Transactions on Control of Network Systems" date=" vol. 12, no. 2, pp. 1381-1392, June 2025" pdf="tcns-2024.pdf"> | ||
| + | Live Streaming Synchronisation Using Event-triggered Consensus Control | ||
</paper> | </paper> | ||
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===2024=== | ===2024=== | ||
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<paper authors="M.A. Rezaei, G. Manfredi, V. A. Racanelli, S. Mascolo, L. De Cicco" conference="Proc. of International Conference on | <paper authors="M.A. Rezaei, G. Manfredi, V. A. Racanelli, S. Mascolo, L. De Cicco" conference="Proc. of International Conference on | ||
Unmanned Aircraft Systems (ICUAS 2024)" place="Chania, Greece" date="June 2024" pdf="icuas24.pdf"> | Unmanned Aircraft Systems (ICUAS 2024)" place="Chania, Greece" date="June 2024" pdf="icuas24.pdf"> | ||
|
Vito Andrea Racanelli |
| Eng, PhD, Researcher |
Researcher working in the fields of control theory, robotics, and autonomous systems. He is currently a visiting postdoctoral researcher at Carleton University (Canada) and collaborates with the C3Lab at the Polytechnic University of Bari, where he received his master's degree cum laude in Automation Engineering, followed by his Ph.D. in Industry 4.0 in January 2025.
His main research interests include Model Predictive Control (MPC), Reinforcement Learning, and data-driven control methods. From an applied perspective, his work focuses on the implementation of automation algorithms on drones (UAVs), mobile robotics platforms, and video streaming systems.
He is a member of ACM, IEEE, and IFAC. Over the course of his academic career, he has authored and co-authored several scientific papers presented at conferences and published in academic journals. His research primarily explores the integration between traditional control engineering techniques and artificial intelligence for industrial applications.|
|
Vito Andrea Racanelli |
| Eng, PhD, Researcher |
Researcher working in the fields of control theory, robotics, and autonomous systems. He is currently a visiting postdoctoral researcher at Carleton University (Canada) and collaborates with the C3Lab at the Polytechnic University of Bari, where he received his master's degree *cum laude* in Automation Engineering, followed by his Ph.D. in Industry 4.0 in January 2025.
His main research interests include Model Predictive Control (MPC), Reinforcement Learning, and data-driven control methods. From an applied perspective, his work focuses on the implementation of automation algorithms on drones (UAVs), mobile robotics platforms, and video streaming systems.
He is a member of ACM, IEEE, and IFAC. Over the course of his academic career, he has authored and co-authored several scientific papers presented at conferences and published in academic journals. His research primarily explores the integration between traditional control engineering techniques and artificial intelligence for industrial applications.