Maria Lombardi
Papers
8
Total Citations
64
H-Index
5
About
Maria Lombardi is a pioneering researcher at the intersection of social robotics, human-robot interaction, and complex human networks. Her work fundamentally explores how humans and artificial agents synchronize, coordinate, and communicate through non-verbal cues. Lombardi’s most influential study, “Spontaneous emergence of leadership patterns drives synchronization in complex human networks” (21 citations), reveals how motor coordination naturally arises in groups—from rocking chairs to violin players—and how coupling structure shapes collective behavior. She has made landmark contributions to attentive robotics, developing learning-based systems that enable humanoid robots like the iCub to estimate mutual gaze and detect objects humans are looking at using only visual feedback. Her 2022 paper on mutual gaze estimation (14 citations) and her pipeline for human attention estimation (2024) are foundational for creating robots that can engage in joint attention and collaborative tasks. Lombardi has also advanced the study of Sense of Agency in human-robot interaction, showing how a robot’s facial expressions and communicative gaze influence a person’s feeling of control over joint actions. Her work on deep learning control of artificial avatars in multi-agent motor tasks (2021) extends coordination research to group scenarios with multiple artificial agents. With a growing citation record and a focus on making robots socially aware partners, Lombardi is shaping the future of collaborative robotics and human-machine teams.
Research Focus
Key Achievements
Top Papers
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- 7Deep learning control of artificial avatars in group coordination tasks3 citations · 2019
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