Papers
4
Total Citations
95
H-Index
4
About
Amir Dini is a researcher specializing in human-robot interaction (HRI) and human-robot collaboration (HRC), with a particular focus on cognitive and attentional processes that shape how humans and robots work together. His most significant contributions center on developing innovative, real-time methodologies for measuring and predicting situation awareness — a critical factor in optimizing collaborative human-robot systems. Dini's landmark work, published in 2017, introduced a probabilistic framework for assessing situation awareness from gaze features captured via eye-tracking glasses and 3D gaze analysis, each garnering 33 citations. These studies established a compelling link between human attention patterns and overall system performance, offering researchers and engineers a powerful tool for evaluating HRI in dynamic environments. He extended this foundation in 2019, broadening the framework to incorporate both eye and head gaze signals, enabling richer estimation of situation awareness scores and user performance metrics — work that has since attracted an additional 29 citations combined. Across his body of work, Dini has championed real-time, non-intrusive assessment of human cognitive states, making his research particularly valuable for designing intuitive, safer, and more efficient collaborative robot systems. His contributions provide a practical bridge between human factors science and modern robotics engineering.
Research Focus
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