MBZUAI alumnus Adnan Khan is pursuing a Ph.D. at Carleton University, focusing his research on using computer vision to improve accessibility in healthcare, particularly for the visually impaired. His work builds upon his master's thesis at MBZUAI, which focused on domain generalization, enabling models to adapt across different data domains. Khan credits his experiences at MBZUAI for shaping his community spirit and career path. Why it matters: This highlights the role of AI education in fostering socially impactful research and driving innovation in healthcare accessibility in the region and beyond.
MBZUAI alumnus Ahmed Sharshar is developing smaller AI models to make the technology more accessible, especially in resource-constrained environments like Egypt. His master's thesis involved creating an app that assesses lung health using mobile phone video analysis, eliminating the need for traditional medical devices. Sharshar is pursuing his Ph.D. at MBZUAI, focusing on lightweight and energy-efficient models for various applications. Why it matters: Democratizing AI through smaller, efficient models can enable broader applications and innovation across diverse sectors in the Middle East and beyond.
MBZUAI alumnus Ikboljon Sobirov is using AI to develop new diagnostic tools for cardiovascular disease at the University of Oxford. His research focuses on building imaging biomarkers by integrating transcriptomic data with medical scans. The goal is to predict how a patient will respond to specific medications using only images. Why it matters: This work showcases the potential of AI and multi-modal data to personalize medicine and improve healthcare outcomes in the region and globally.
MBZUAI alumnus Numan Saeed is applying machine learning to medical imaging and cancer research as a research scientist at the University. He collaborates with UAE hospitals like Sheikh Shakhbout Medical City and Cleveland Clinic to build datasets and gather clinical feedback. Saeed's team is developing a model focused on head and neck cancer using the HECKTOR dataset and local data. Why it matters: This research contributes to the UAE's healthcare ambitions by enabling earlier diagnosis and personalized care through AI-driven analysis of medical images.
MBZUAI alumna Akbobek Abilkaiyrkyzy, who graduated with a master's in machine learning in 2022, has been involved in various domains, including industry, entrepreneurship, and sustainability. Her master's thesis focused on developing a chatbot for mental health problem detection, leading to the creation of WellRound, an app that uses data from various sources to improve mental and physical wellbeing. She further developed the app with support from the MBZUAI Incubation and Entrepreneurship Center (MIEC). Why it matters: This highlights MBZUAI's role in fostering AI innovation and entrepreneurship in the healthcare sector, as well as empowering its graduates to create solutions addressing critical societal needs.