Mimouna Abdullah Alkhonaini
Papers
1
Total Citations
19
H-Index
1
About
Dr. Mimouna Abdullah Alkhonaini is a leading researcher at the intersection of artificial intelligence and brain-computer interfaces (BCIs), with a primary focus on enhancing communication systems for individuals with motor disabilities. Her most cited work, "Arithmetic Optimization with RetinaNet Model for Motor Imagery Classification on Brain Computer Interface" (2022, 19 citations), introduces a novel hybrid approach that combines arithmetic optimization algorithms with advanced deep learning architectures to improve the classification of motor imagery tasks from EEG signals. This contribution directly addresses a critical bottleneck in BCI technology—the accurate and efficient decoding of brain signals to enable seamless control of assistive robots and communication devices. Dr. Alkhonaini’s research demonstrates how optimization techniques can significantly boost the performance of neural network models, paving the way for more reliable, real-time BCI applications. Her work is particularly impactful for the development of non-invasive, EEG-based systems that empower individuals with severe movement impairments to interact with their environment. By bridging computational optimization and neuroengineering, Dr. Alkhonaini is advancing the practical deployment of BCIs in clinical and assistive technology settings, making her a notable figure in the field of human-computer interaction.
Research Focus
Key Achievements
Top Papers
- 1