Vitoantonio Bevilacqua
Papers
13
Total Citations
746
H-Index
8
About
Vitoantonio Bevilacqua is an Italian researcher whose work spans the intersection of artificial intelligence, computer vision, and human-machine interaction, with particular emphasis on biomedical robotics and rehabilitation engineering. He is perhaps best known for his highly influential 2018 survey on pedestrian detection and tracking using deep learning and computer vision techniques, which has accumulated over 530 citations and stands as a landmark reference in the field. Equally significant is his sustained research into myoelectric control systems, where he has pioneered approaches to decoding human motor intent from EMG signals using muscle synergy extraction and autoencoder-based neural models — work with meaningful implications for prosthetics, exoskeletons, and wearable rehabilitation devices. His 2018 neuromusculoskeletal modeling study and subsequent synergy-to-force mapping contributions reflect a coherent research vision: enabling more natural, intuitive control of assistive robotic systems. Bevilacqua has also contributed to robot-assisted surgery through deep learning-based image processing frameworks and to industrial automation via AI-driven depalletization strategies. Across more than a decade of research, his work bridges fundamental computational methods and real-world applications in healthcare and robotics, demonstrating both scientific depth and strong translational impact.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9A Robust Real-Time 3D Tracking Approach for Assisted Object Grasping8 citations · 2014
- 10