Papers
12
Total Citations
132
H-Index
7
About
Umar Shahbaz Khan is a prolific researcher whose work spans robotics, computer vision, human-computer interaction, and intelligent systems. His research has made significant contributions to human activity recognition (HAR), where his 2019 paper on 2D skeleton data and supervised machine learning has garnered 41 citations, establishing him as a notable voice in vision-based recognition systems applicable to surveillance, telecare, and ambient intelligence. Khan has also advanced the field of mobile robotics, with multiple contributions to Simultaneous Localization and Mapping (SLAM), including sensor evaluation using Analytical Hierarchy Process and multi-sensor navigation frameworks, collectively accumulating over 30 citations. His work in Brain-Computer Interfaces (BCI) is particularly forward-looking, addressing motor imagery classification and SSVEP-based systems to empower individuals with motor disabilities through assistive technologies. Additional contributions include object detection using monocular cameras, fuzzy logic-based robot navigation under uncertainty, and agricultural robotics in simulated environments. With over 127 total citations and a research trajectory spanning more than a decade, Khan's interdisciplinary expertise bridges theoretical innovation and practical robotic implementation, making his work highly relevant to students and researchers in AI, robotics, and assistive technology.
Research Focus
Key Achievements
Top Papers
- 1
- 2Investigation of Widely Used SLAM Sensors Using Analytical Hierarchy Process16 citations · 2022
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- 5Multi-Sensor SLAM for efficient Navigation of a Mobile Robot9 citations · 2021
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- 8Z-Number-Based Fuzzy Logic Approach for Mobile Robot Navigation7 citations · 2023
- 9
- 10Design of non-conventional chain drive mechanism for a mini-robot6 citations · 2012