Barbara Di Eugenio
Papers
8
Total Citations
56
H-Index
4
About
Barbara Di Eugenio is a prominent researcher whose work sits at the intersection of human-robot interaction, multimodal communication, and assistive robotics. Her research focuses on enabling robots to collaborate naturally and effectively with humans—particularly older adults and people with disabilities—through rich, multi-channel communication that combines language, gesture, haptic cues, and physical action. Among her most significant contributions is the development of a Multimodal Interaction Manager (MIM) for assistive robots, which addresses the complex challenge of managing dynamic role-switching between human and robot collaborators during everyday tasks. Her foundational investigations into haptic-ostensive actions and physical manipulation have shed light on how humans communicate through touch and force exchanges, providing a basis for more naturalistic robot behavior. More recently, Di Eugenio has advanced the field through neural network-based human simulators and multimodal reinforcement learning frameworks, enabling robots to be trained in realistic interactive environments without costly real-world data collection. Her work, spanning nearly a decade of peer-reviewed publications, has accumulated citations across robotics, dialogue systems, and human-computer interaction communities. Di Eugenio's research represents a sustained and impactful effort to close the gap between human social fluency and robotic capability.
Research Focus
Key Achievements
Top Papers
- 1A Multimodal Human-Robot Interaction Manager for Assistive Robots16 citations · 2019
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- 3Role Switching in Task-Oriented Multimodal Human-Robot Collaboration12 citations · 2020
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- 7Multimodal Reinforcement Learning for Robots Collaborating with Humans2 citations · 2023
- 8Multimodal Reinforcement Learning for Robots Collaborating with Humans1 citations · 2025