Papers
11
Total Citations
86
H-Index
7
About
Dario Cazzato’s research lies at the intersection of human-robot interaction, computer vision, and socially assistive robotics, with a particular focus on supporting individuals with Autism Spectrum Disorders (ASD). His work is distinguished by its practical, low-cost approach to enabling robots to perceive and respond to human social cues. Cazzato pioneered a calibration-free gaze estimator for soft biometrics (12 citations), allowing robots to infer gender and age from natural interactions. He made significant contributions to joint attention detection—a critical skill for social communication—by developing systems that enable humanoid robots to automatically detect when a person shares attention with them (10 citations). His assistive robotics platform integrates RGB-D sensors and graphical user interfaces to encourage communication in ASD populations, notably implementing a digital version of the Picture Exchange Communication System (PECS) therapy (9 citations). Cazzato also advanced autonomous navigation with deep learning-based semantic situation awareness for aerial robots using LIDAR (7 citations). Across his most cited works, he has accumulated over 80 citations, demonstrating the growing impact of his vision for socially aware, assistive robotic systems that bridge technology and human developmental needs.
Research Focus
Key Achievements
Top Papers
- 1
- 2Automatic Joint Attention Detection During Interaction with a Humanoid Robot10 citations · 2015
- 3
- 4
- 5Real-Time Gender Based Behavior System for Human-Robot Interaction9 citations · 2014
- 6
- 7Faster Visual-Based Localization with Mobile-PoseNet7 citations · 2019
- 8
- 9Soft Biometrics for a Socially Assistive Robotic Platform6 citations · 2015
- 10