Hanin Ahmed, a KAUST Ph.D. graduate in plant science, is now an Ibn-Rushd Postdoctoral Fellow at The Centre for Anthropology and Genomics of Toulouse, France. Her Ph.D. research at KAUST focused on the population genomics and evolutionary history of fonio millet and einkorn wheat. One key finding was the influence of ethnic groups on the genetic diversity of fonio millet, and insights into wheat adaptation during early agriculture from einkorn wheat research published in Nature. Why it matters: This highlights KAUST's role in training researchers who are contributing to advancements in genomics and agriculture, with implications for crop improvement and understanding the impact of social factors on plant genetics.
KAUST alumna Dr. Hanin Ahmed has been awarded a Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship to research the biological traits, ancestry, and symbolic roles of horses used in ancient rituals. She will analyze DNA samples from 97 sites across France, linking biology with ritual behavior. Ahmed previously held an Ibn Rushd Fellowship from KAUST, which supported her move to the University of Toulouse. Why it matters: This prestigious fellowship highlights the quality of research and training at KAUST while enabling exploration of the co-evolution of humans and animals through genomics and archaeology.
MBZUAI alumnus Hanan Gani, a 2024 master's graduate in machine learning, is now a research associate at MBZUAI working on a meteorological project with the UAE government. He also focuses on multimodal and embodied intelligence research, mentors AI students, and has published nine papers during his time at MBZUAI. His research includes work on vision transformers, text-to-image generation, and large multimodal models. Why it matters: Showcases MBZUAI's role in attracting and developing AI talent within the UAE, contributing to the nation's AI research capabilities.
Ghada Ahmed, a fourth-year Ph.D. student at KAUST's Solar Center, researches semiconductor nanocrystals under the supervision of Assistant Professor Omar Mohammed. Her work focuses on the colloidal synthesis of quantum dots and nanocrystals with controlled sizes and shapes. She aims to understand photogenerated charge carrier dynamics and reaction mechanisms to optimize energy-efficient devices. Why it matters: This research contributes to advancements in materials science and renewable energy technologies within the Kingdom.
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.
The paper introduces Juhaina, a 9.24B parameter Arabic-English bilingual LLM trained with an 8,192 token context window. It identifies limitations in the Open Arabic LLM Leaderboard (OALL) and proposes a new benchmark, CamelEval, for more comprehensive evaluation. Juhaina outperforms models like Llama and Gemma in generating helpful Arabic responses and understanding cultural nuances. Why it matters: This culturally-aligned LLM and associated benchmark could significantly advance Arabic NLP and democratize AI access for Arabic speakers.