Leilani H. Gilpin
Papers
1
Total Citations
2
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1
About
Leilani H. Gilpin is a leading researcher in explainable artificial intelligence (XAI), with a focus on making autonomous systems transparent, interpretable, and aligned with human values. Her work bridges AI reasoning, human-robot interaction, and knowledge-driven systems, particularly in socially assistive robotics. In her notable 2020 paper, "A Knowledge Driven Approach to Adaptive Assistance Using Preference Reasoning and Explanation," Gilpin addresses the critical need for socially assistive robots to explain their behavior in ways that reflect user preferences and goals. This work contributes to building AI systems that are not only intelligent but also trustworthy and user-centered. Though early in its citation impact, the paper represents a foundational step toward interpretable reasoning in adaptive assistance. Gilpin’s broader contributions include advancing methods for AI transparency, developing frameworks for preference-based explanation, and promoting ethical AI design. Her research is essential for students and practitioners working at the intersection of AI, robotics, and human-centered computing, offering a roadmap for creating machines that can reason, adapt, and explain their decisions in socially meaningful ways.
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