Papers
9
Total Citations
82
H-Index
5
About
Aakash Yadav is a pioneering researcher at the intersection of human-robot interaction (HRI), cognitive neuroscience, and autonomous systems. His work fundamentally advances how robots perceive, adapt to, and collaborate with humans in high-stakes environments. Yadav’s major contributions lie in developing non-invasive methods to measure and model human trust and cognitive states during human-robot teaming. He has pioneered the use of eye tracking, physiological indicators, and even brain-behavior relationships to quantify dynamic trust—moving beyond traditional self-reports to create real-time, objective measures. His most cited work, "Image-based flight control of UAVs for material handling in custom manufacturing" (29 citations), showcases his early expertise in autonomous systems. However, his core impact is in HRI, where papers like "In Gaze We Trust" (17 citations) and "Brain–Behavior Relationships of Trust" (10 citations) have shaped the field. Notably, his research on robot adaptation using reinforcement learning to mitigate operator cognitive fatigue represents a critical step toward truly collaborative, human-aware robots. With applications spanning search and rescue, disaster response, and manufacturing, Yadav’s work is essential reading for anyone interested in building trustworthy, intelligent robotic teammates.
Research Focus
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Top Papers
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- 9Interplay of Cognitive Fatigue and Trust in Human-Robot Collaboration2 citations · 2022