Yusra Abdulrahman
Papers
9
Total Citations
91
H-Index
5
About
Yusra Abdulrahman is an emerging researcher at the forefront of robotic perception, neuromorphic vision, and intelligent manufacturing automation. Her work focuses on developing advanced sensing technologies that bridge the gap between human-like dexterity and machine precision, with particular emphasis on aerospace and industrial applications. Abdulrahman has made significant contributions to vision-based tactile sensing, introducing innovations such as TactiGraph — an asynchronous graph neural network leveraging neuromorphic cameras for contact angle prediction — and a multi-layered vision-based tactile sensor that simultaneously enhances sensitivity and measurement range. Her research into neuromorphic vision has yielded high-speed countersink inspection systems capable of meeting the stringent demands of aerospace assembly lines, accumulating over 20 citations since 2023. Abdulrahman has also advanced collaborative robot precision through novel multi-functional vision sensors for normality and position measurement, and contributed a large-scale event camera dataset, E-POSE, to support object pose estimation research. With a growing citation record spanning robotics, machine vision, and tactile sensing, her work is helping redefine the capabilities of intelligent robotic systems in high-stakes manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7E-POSE: A Large Scale Event Camera Dataset for Object Pose Estimation4 citations · 2025
- 8
- 9