Papers
2
Total Citations
63
H-Index
2
About
Nadeem Ahmed is a leading researcher in Human Activity Recognition (HAR) and Human-Robot Interaction (HRI), with a focus on developing intelligent, sensor-driven systems for real-world applications. His most-cited work, a 2020 paper on robust feature extraction using 3-axis accelerometer and gyroscope data (48 citations), has significantly advanced HAR for healthcare monitoring, security, and robotics by enabling accurate characterization of human behavior from smartphone and smartwatch sensors. In 2019, Ahmed introduced a novel dynamic hand gesture and movement trajectory recognition model for non-touch HRI interfaces (15 citations), addressing a critical need for intuitive, sensor-free control of semi-autonomous robots. This work stands out for its potential to enhance safety and accessibility in industrial and assistive robotics. With a growing citation impact, Ahmed’s contributions bridge the gap between embedded sensing and practical automation, offering scalable solutions for elderly care, employee monitoring, and gesture-based control. His research continues to shape how machines understand and respond to human movement, making him a notable figure in the intersection of pervasive computing and interactive robotics.
Research Focus
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Top Papers
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