Researcher and Assistant Professor, Politecnico di Bari, Italy
Agostino Giorgio, a distinguished Researcher and Assistant Professor at Politecnico di Bari, Italy, holds a Ph.D. in Electronics Engineering and leads the Digital Electronics Lab since 2020. Born in Bari, Italy, in 1969, his career spans pivotal advancements in embedded systems, FPGA implementations, AI applications, nanoelectronics, and quantum computing. His innovative contributions extend to telemedicine, home care, and personal safety electronics.
Profile
Scopus
Education📚
Agostino Giorgio completed his Laurea degree with honors in Electronic Engineering from the Polytechnic of Bari in 1994, followed by a Ph.D. in Electronics Engineering in 1998. His academic journey laid the foundation for his extensive research and teaching career.
Experience 💼
Since 1998, Agostino Giorgio has served as a Researcher and Assistant Professor at Politecnico di Bari, where he pioneers research in digital electronics and its applications. He has spearheaded numerous projects and collaborations, notably with the National Institute of Nuclear Physics and AstraZeneca, contributing significantly to fields like particle accelerators for tumor therapy and telemonitoring systems for heart failure.
Research Interests 🔬
Agostino Giorgio’s research interests encompass embedded systems, FPGA design, AI implementation on microcontrollers, quantum computing, and digital electronics for telemedicine and home care applications. His work focuses on advancing technology’s role in enhancing healthcare and safety systems.
Awards 🏆
Agostino Giorgio has earned acclaim for his research contributions, including his nomination for the Best Researcher Award, recognizing his innovations in AI-driven personal safety devices and quantum computing emulation.
Publications
IEEE Access (2024): “Project and Implementation of a Quantum Logic Gate Emulator on FPGA Using a Model-Based Design Approach” – cited by 0 articles.
Journal of Low Power Electronics and Applications (2023): “FPGA-Based Decision Support System for ECG Analysis” – cited by 7 articles.
International Journal of Biomedical Engineering and Technology (2023): “Artificial intelligence methods for image classification applied to biological sounds for the early diagnosis of cardiorespiratory pathologies and COVID-19 infection” – cited by 0 articles.