Dr. Ghada Al-Hudhud
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Dr. Ghada Al-Hudhud

Professor
Department of Information Technology, King Saud University, Riyadh, Saudi Arabia


Highest Degree
Ph.D. in Software Engineering from De Montfort University, UK

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Area of Interest:

Computer Sciences
100%
Brain Computer Interface
62%
Information Technology
90%
Human Computer Interactions
75%
Face Recognition
55%

Research Publications in Numbers

Books
2
Chapters
2
Articles
25
Abstracts
0

Selected Publications

  1. Alshathri, D.M., A.S. Alhumaimeedy, G. Al-Hudhud, A. Alsaleh, S. Al-Musharaf and G.S. Aljuraiban, 2020. Weight management apps in Saudi Arabia: Evaluation of features and quality. JMIR Mhealth Uhealth, Vol. 8. 10.2196/19844.
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  2. Alshathri, D.M., A.S. Alhumaimeedy, G. Al-Hudhud, A. Alsaleh, S. Al-Musharaf and G.S. Aljuraiban, 2020. Weight management apps in Saudi Arabia: Evaluation of features and quality (preprint). JMIR Mhealth Uhealth, Vol. 8. 10.2196/preprints.19844.
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  3. Al Hudhud, G. and H. Chorfi, 2019. Smart adaptive learning management application. Biom. Biostat. Int. J., 6: 454-461.
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  4. Al-Hudhud, G., 2017. Affective Quality Assessment for Android Applications Using Q Sensor Biostat. Biom. Open Access J., Vol. 2. 10.19080/BBOAJ.2017.02.555576.
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  5. Alhuhud, G. and W. Altamimi, 2016. Quality evaluation of mobile game: Miftah Alfasaha. Mobile Inf. Syst., Vol. 2016. 10.1155/2016/4581279.
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  6. Al-Hudhud, G., 2015. Designing e-Coordinator for improved teams collaboration in graduation project. Comput. Hum. Behav., 51: 640-644.
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  7. Al-Hudhud, G., 2015. Aspect oriented design for team learning management system. Comput. Hum. Behav., 51: 627-631.
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  8. Al-Hudhud, G., M.A. Alzamel, E. Alattas and A. Alwabil, 2014. Using brain signals patterns for biometric identity verification systems. Comput. Hum. Behav., 31: 224-229.
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  9. Al-Hudhud, 2014. Affective command-based control system integrating brain signals in commands control systems. G., 30: 535-541.
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  10. Al-Hudhud, G., M.K. Ibrahim and M. Al-Akaidi, 2010. Automatic production of quantisation matrices based on perceptual modelling of wavelet coefficients for grey scale images. Image Vision Comput., 28: 644-653.
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