{"id":21016,"date":"2026-01-05T22:01:52","date_gmt":"2026-01-05T19:01:52","guid":{"rendered":"https:\/\/su.edu.ye\/fcit\/?p=21016"},"modified":"2026-01-05T22:01:52","modified_gmt":"2026-01-05T19:01:52","slug":"masters-degree-awarded-to-ms-somaya-abdo-al-bahri-in-information-technology","status":"publish","type":"post","link":"https:\/\/su.edu.ye\/fcit\/en\/21016\/","title":{"rendered":"Master\u2019s Degree Awarded to Ms. Somaya Abdo Al-Bahri \u200e in Information Technology"},"content":{"rendered":"<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Ms. Somaya Abdo Ahmed Al-Bahri \u200e<\/strong>was awarded a Master\u2019s Degree in <strong>Information Technology <\/strong>for her thesis titled: <strong><em>Improving Identity Verification Systems Using Cross-Generational Face Recognition: Integrating Contrastive Learning with Generative Adversarial Networks (GANs)<\/em><\/strong><em>, <\/em>which was submitted to the Department of Information Technology, Faculty of Computer Science and Information Technology \u2013 Sana\u2019a University. The MA defense was held on <strong>Monday, December 1, 2025.<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p>The MA Viva-voce Committee, which was formed based on a resolution issued by the Graduate Studies and Scientific Research Council, consisted of the following:<\/p>\n<table>\n<tbody>\n<tr>\n<td><strong>#<\/strong><\/td>\n<td><strong>Committee Members<\/strong><\/td>\n<td><strong>Designation<\/strong><\/td>\n<td><strong>Position<\/strong><\/td>\n<\/tr>\n<tr>\n<td>1<\/td>\n<td><strong>Prof. Ibrahim Ahmed Al-Baltah \u200e<\/strong><\/td>\n<td>Internal Examiner<\/td>\n<td>Chair<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td><strong>Prof. Naji Ali Al-Shaibani \u200e<\/strong><\/td>\n<td>Main Supervisor<\/td>\n<td>Member<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td><strong>Assoc. Prof. Khalil Saeed Al-Wajeeh \u200e<\/strong><\/td>\n<td>External Examiner<\/td>\n<td>Member<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>The study aimed to:<\/p>\n<ul>\n<li>Analyze the impact of aging by examining how facial aging affects facial features \u200eand the accuracy of face recognition systems.\u200e<\/li>\n<li>Develop intelligent techniques by designing models\u2014such as Generative \u200eAdversarial Networks (GANs)\u2014capable of extracting personal identity \u200eindependently of age-related variations.\u200e<\/li>\n<li>Provide comprehensive datasets by compiling diverse databases (covering different \u200eages, ethnicities, and lighting conditions) to ensure robust performance under real-\u200eworld scenarios.\u200e<\/li>\n<li>Test and evaluate performance by measuring the efficiency of the proposed models \u200eusing internationally recognized benchmarks to verify their superiority over \u200eexisting systems.\u200e<\/li>\n<\/ul>\n<p>The study findings demonstrated, through experimental evaluation using 5-fold cross-validation, that the proposed model outperformed existing approaches by a margin ranging from 2% to 5% in cross-database verification tests (FG \u21d2 MO and MO \u21d2 FG).<\/p>\n<p>In light of the findings, the researcher recommended:<\/p>\n<ul>\n<li>Implementing pilot testing and scalability assessment by deploying the system in a \u200elimited real-world environment.\u200e<\/li>\n<li>Designing a flexible and scalable system architecture capable of efficiently \u200ehandling millions of verification requests.\u200e<\/li>\n<li>Adopting high-performance computing (HPC) infrastructure to enhance \u200eprocessing speed and system reliability.\u200e<\/li>\n<li>Ensuring security, privacy, and ethical compliance through the activation of end-\u200eto-end data encryption.\u200e<\/li>\n<\/ul>\n<p>The defense session was attended by a number of academics, researchers, students, colleagues, and the researcher\u2019s family.<\/p>\n<p><img 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Technology for her thesis titled: Improving &hellip; <\/p>\n","protected":false},"author":128,"featured_media":21012,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[121],"tags":[],"class_list":["post-21016","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-2"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.10 - aioseo.com -->\n\t<meta name=\"description\" content=\"Ms. Somaya Abdo Ahmed Al-Bahri \u200ewas awarded a Master\u2019s Degree in Information Technology for her thesis titled: Improving Identity Verification Systems Using Cross-Generational Face Recognition: Integrating Contrastive Learning with Generative Adversarial Networks 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