Mansour Alsulaiman
Papers
25
Total Citations
1,353
H-Index
14
About
Mansour Alsulaiman is a prominent researcher whose work spans brain-computer interfaces (BCIs), agricultural robotics, and autonomous mobile systems. He has made particularly significant contributions to the intersection of deep learning and biomedical signal processing, most notably through his highly cited 2021 review of deep learning techniques for EEG-based motor imagery classification, which has accumulated over 558 citations and serves as a foundational reference in the BCI community. His subsequent work on dynamic convolution with multilevel attention for EEG decoding further advances the field's ability to interpret brain signals for assistive technologies. Alsulaiman has also pioneered the application of computer vision and deep learning to precision agriculture, developing intelligent systems for date fruit classification and robotic harvesting — a particularly impactful contribution given Saudi Arabia's substantial date palm industry. His publicly released date fruit dataset has enabled reproducible research across the field. Earlier in his career, he established expertise in autonomous mobile robotics, contributing fuzzy logic and D*-based path-planning algorithms for navigation in dynamic environments. With a citation profile exceeding 1,200 across diverse domains, Alsulaiman exemplifies the power of applying AI-driven methodologies to real-world engineering and healthcare challenges.
Research Focus
Key Achievements
Top Papers
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- 5Date fruit dataset for intelligent harvesting69 citations · 2019
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- 7D* Lite Based Real-Time Multi-Agent Path Planning in Dynamic Environments54 citations · 2011
- 8Multi-CNN Feature Fusion for Efficient EEG Classification38 citations · 2020
- 9Attention based Inception model for robust EEG motor imagery classification32 citations · 2021
- 10A Hierarchical Fuzzy Control Design for Indoor Mobile Robot29 citations · 2014