Papers
9
Total Citations
328
H-Index
6
About
Neta Ezer is a prominent researcher whose work spans human-robot interaction, aging and technology acceptance, autonomous systems, and machine learning for robotics. Her early and most influential contributions focused on understanding how people of different ages perceive and accept domestic robots. Her 2009 study on attitudinal and intentional acceptance of robots by younger and older adults has garnered 126 citations, establishing her as a leading voice in age-inclusive robot design. Complementary work explored the nuanced question of what tasks individuals are willing to delegate to robots — moving beyond simple appliance-like functions toward interactive and critical roles — accumulating an additional 70+ citations across related publications. Ezer also investigated age-related differences in whether people conceptualize robots as appliances, teammates, or friends, providing foundational insights for developers of assistive technologies. Her research expanded into unmanned aerial vehicle (UAV) systems, with a 2021 study on adaptive human-robot interactions for multi-UAV operations earning 46 citations. More recently, she contributed to robot learning methodology through work on sparse demonstration techniques using Pontryagin differentiable programming. Her NASA-affiliated research on space robotics further underscores the breadth and real-world significance of her interdisciplinary contributions.
Research Focus
Key Achievements
Top Papers
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- 3Adaptive Human-Robot Interactions for Multiple Unmanned Aerial Vehicles46 citations · 2021
- 4Learning From Sparse Demonstrations32 citations · 2022
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- 7Learning from Sparse Demonstrations5 citations · 2020
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