Gennaro De Luca
Papers
11
Total Citations
198
H-Index
8
About
Gennaro De Luca is a leading researcher at the intersection of quantum computing, artificial intelligence, and robotics, with a particular focus on making these advanced technologies accessible for education and real-world applications. His most impactful work includes a highly cited survey on NISQ-era hybrid quantum-classical machine learning (59 citations), which has become a foundational resource for researchers navigating the practical challenges of near-term quantum devices. De Luca is perhaps best known for creating VIPLE (Visual IoT/Robotics Programming Language Environment), a visual programming platform that has transformed computer science education by enabling students to program diverse IoT devices and robots without deep coding expertise. His contributions extend to assistive technology, including a guide-dog robot system that integrates traffic light and moving object detection to aid visually impaired individuals. With over 196 total citations across his top works, De Luca has also advanced smart city technologies, concurrent computing verification, and dynamic traffic routing simulations. His work uniquely bridges theoretical foundations—such as applying pi-calculus to IoT programming—with practical, deployable systems, making him a pivotal figure in democratizing robotics and quantum computing education.
Research Focus
Key Achievements
Top Papers
- 1Survey of NISQ Era Hybrid Quantum-Classical Machine Learning Research59 citations · 2021
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- 5Traffic light and moving object detection for a guide‐dog robot16 citations · 2020
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- 7Visual IoT/Robotics Programming Language in Pi-Calculus9 citations · 2017
- 8Traffic Dataset for Dynamic Routing Algorithm in Traffic Simulation8 citations · 2022
- 9Technologies for developing a smart city in computational thinking3 citations · 2018
- 10Technologies for developing a smart city in computational thinking2 citations · 2018