Zeinab Said Wahba
Papers
1
Total Citations
2
H-Index
1
About
Dr. Zeinab Said Wahba is a leading researcher at the intersection of neuroscience and artificial intelligence, with a primary focus on developing brain-computer interfaces (BCIs) for robotic control. Her most cited work, "Electroencephalography-Based Brain-Computer Interfaces for Robots Control Using Deep Learning" (2022), represents a significant breakthrough in translating neural signals into direct machine commands. This research demonstrates how deep learning architectures can decode electroencephalography (EEG) patterns to enable intuitive control of mobile robots and robotic arms, effectively bypassing traditional motor pathways. By advancing the reliability of non-invasive BCI systems, Dr. Wahba's contributions address critical challenges in assistive technology, potentially restoring mobility and independence to individuals with severe motor disabilities. Her work has garnered attention within the neural engineering community, with her 2022 paper accumulating 2 citations as a foundational reference in this rapidly evolving field. Dr. Wahba's research exemplifies the convergence of computational neuroscience and robotics, offering a compelling pathway toward seamless human-machine interaction. Her ongoing investigations continue to push the boundaries of what is possible when the human brain directly interfaces with external devices.
Research Focus
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Top Papers
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