Gioacchino Manfredi

Gioacchino Manfredi is an Assistant Professor in the Department of Electrical and Information Engineering at the Polytechnic of Bari, Italy. His academic work focuses on the intersection of control theory, machine learning, and networked systems, with particular emphasis on video streaming technologies and biomedical applications.

Dr. Manfredi earned his cum laude degree in Control Engineering from Sapienza University of Rome in October 2018, where he was later awarded the "excellent graduate" prize in March 2019. He completed his Ph.D. in Electric and Information Engineering at the Polytechnic of Bari in 2023.

His research spans multiple domains with a strong focus on adaptive video streaming systems, where he has made significant contributions to QoE (Quality of Experience) and QoS (Quality of Service) management. His work extends to deep reinforcement learning applications for nonlinear control systems, particularly in medical contexts like automated insulin delivery for diabetes treatment. Additional research interests include consensus algorithms for multi-agent systems, 360° video streaming, and Lyapunov Neural Networks for stability analysis of nonlinear systems.

Dr. Manfredi's publication record demonstrates a clear evolution from traditional network control systems toward more sophisticated AI-driven approaches, with recent work bridging theoretical control concepts with practical implementations in both networked multimedia and biomedical systems. His research shows increasing sophistication in applying reinforcement learning to safety-critical domains while maintaining rigorous stability guarantees.

• Excellent Graduate Prize from Sapienza University of Rome (2019)

As an active member of the C3 Lab at Polytechnic of Bari, Dr. Manfredi collaborates closely with Professor Saverio Mascolo and other researchers on projects related to low-delay protocols, adaptive video streaming, and congestion control. His work contributes to several research initiatives including those focused on real-time communication systems and medical cyber-physical applications, demonstrating the versatility of control theory approaches across diverse application domains.