Gianluca Giuffrida

About

Gianluca Giuffrida is a leading researcher in assistive robotics and human–machine interaction, with a focus on empowering individuals with upper limb disabilities. His key contributions lie at the intersection of computer vision and robotic control, particularly through the application of convolutional neural networks. His most cited work, "A YOLOv2 Convolutional Neural Network-Based Human–Machine Interface for the Control of Assistive Robotic Manipulators" (2019, 14 citations), addresses a critical challenge: enabling users with reduced manual dexterity to fully exploit the functionalities of modern robotic arms mounted on power wheelchairs. By leveraging real-time object detection, Giuffrida’s interface allows intuitive, vision-based control, bypassing traditional joystick or button inputs. This work has significant implications for improving autonomy and quality of life for individuals with severe motor impairments. Giuffrida’s research is characterized by a practical, user-centered approach, bridging the gap between advanced AI techniques and real-world assistive technologies. His achievements highlight a commitment to inclusive design, making sophisticated robotic systems accessible to those who need them most.

Research Focus

Key Achievements

Top Papers

1. 1
   A YOLOv2 Convolutional Neural Network-Based Human–Machine Interface for the Control of Assistive Robotic Manipulators

   14 citations · 2019

Key Collaborators

Contact & Links