Carmen Bisogni
Papers
5
Total Citations
108
H-Index
5
About
Carmen Bisogni is a leading researcher at the intersection of computer vision, human-robot interaction, and cybersecurity. Her work primarily focuses on monocular vision-aided depth measurement for autonomous systems, particularly for UAV navigation, where she has pioneered methods to achieve depth estimation from single RGB cameras that rival traditional depth sensors. Bisogni is also renowned for her extensive survey on head pose estimation, a foundational work that has garnered 49 citations and serves as a key reference for researchers in the field. Her innovative contributions extend to social robotics, where she explores the dual-use potential of humanoid robots like Pepper—both as tools for enhancing smart ecosystem security through contextual trust models and as vectors for social engineering attacks. Her work on biometric voice mail systems, encrypted via facial recognition, demonstrates a practical application of her research. With over 100 citations across her most-cited papers, Bisogni’s interdisciplinary approach bridges vision, robotics, and security, making her a pivotal figure in advancing autonomous navigation and safe human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5HiMessage: An Interactive Voice Mail System with the Humanoid Robot Pepper10 citations · 2019