MBZUAI hosted its annual Alumni Suhoor, gathering graduates, faculty, staff, and leadership to reconnect and discuss alumni engagement. During the event, the launch of the alumni advisory board was announced, which aims to give alumni a more formal role in shaping engagement strategies and strengthening the University’s global network. The evening included networking sessions to foster new connections and potential collaborations among alumni working in diverse sectors.
MBZUAI alumnus Abdelrahman Shaker discusses his evolving perspective on impactful AI research, shifting from publication counts to real-world usefulness. He highlights the success of his SwiftFormer and EdgeNext papers, which have been adopted by third parties and reached millions of users. Shaker chose MBZUAI for its faculty expertise, which led to 10 publications and over 2,500 citations during his Ph.D.
MBZUAI has completed the second edition of its Global AI Leadership Program (GAILP), designed to equip senior UAE decision-makers with the knowledge to lead in an AI-driven environment. The five-day program included leaders from government, industry, and the innovation ecosystem, with sessions focusing on AI fundamentals, data-driven prediction, workforce transformation, and governance. Participants also discussed the ethical considerations for AI usage.
MBZUAI has launched the Ruwwad AI Scholars (RAIS) program, a postdoctoral fellowship for Emirati Ph.D. graduates to undertake two-year, fully-funded research positions at leading global institutions. The program aims to cultivate local talent in AI and computational research, with the goal of strengthening participants' eligibility for faculty positions at MBZUAI. The fellowship covers a stipend, research funds, insurance, relocation support, and conference travel.
MBZUAI researchers introduce DuwatBench, a new benchmark for multimodal understanding of Arabic calligraphy. The dataset contains 1,272 samples across six calligraphic styles with detailed annotations to evaluate visual-text alignment. Evaluation of 13 multimodal models reveals challenges in processing calligraphic variations and artistic distortions, highlighting the need for culturally grounded AI research.