M. E. Alqaysi
Papers
2
Total Citations
62
H-Index
2
About
M. E. Alqaysi is a researcher at the intersection of artificial intelligence, biomedical engineering, and neurodevelopmental disorders. Their primary research focuses on leveraging AI-based approaches to enhance the diagnosis, triage, and prioritization of autism spectrum disorder (ASD), as evidenced by their highly cited 2023 systematic review, which has garnered 60 citations. This work critically evaluates current trends and open issues in applying machine learning to ASD detection, establishing Alqaysi as a key voice in this emerging field. Additionally, Alqaysi explores the integration of explainable AI with robotic systems, as demonstrated in their 2025 study on adversarial machine learning models for robotic hand control using EEG sensor data fusion. This work addresses critical challenges of trust and interpretability in human-robot interaction, employing fuzzy decision-making to enhance system transparency. By bridging AI, neuroscience, and clinical applications, Alqaysi’s research contributes to both theoretical advancements and practical solutions for improving diagnostic accuracy and assistive technologies. Their work holds significant promise for transforming how neurodevelopmental conditions are identified and managed through intelligent, trustworthy systems.
Research Focus
Key Achievements
Top Papers
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