Irina Rabkina
Papers
1
Total Citations
2
H-Index
1
About
Irina Rabkina is a researcher at the intersection of artificial intelligence, cognitive science, and human-robot interaction, with a primary focus on developing socially assistive robots (SARs) that can reason transparently and adapt to individual users. Her most cited work, "A Knowledge Driven Approach to Adaptive Assistance Using Preference Reasoning and Explanation" (2020), addresses a critical challenge in robotics: the need for SARs to explain their decision-making in ways that reflect a user's personal preferences and goals. This contribution lays the groundwork for more interpretable, user-centered AI systems. While her citation count is still growing—a reflection of the emerging nature of her field—Rabkina's research is foundational for building trust and effective collaboration between humans and assistive technologies. Her work is particularly notable for integrating knowledge-driven reasoning with preference modeling, offering a principled path toward robots that are not only helpful but also understandable. For students and researchers in cognitive robotics and explainable AI, Rabkina’s approach represents a promising direction for creating machines that truly partner with people.
Research Focus
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Top Papers
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