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.
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 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.
Ahmad Alabdulghani, a KAUST master's student in Energy Resources and Petroleum Engineering, is studying fluid flow mechanisms in heterogeneous media under the supervision of Professor Hussein Hoteit. Alabdulghani is a member of the Advanced Reservoir Modeling and Simulation (ARMS) research group at ANPERC. He previously worked at Saudi Aramco's EXPEC Advanced Research Center and aims to pursue a doctorate at KAUST. Why it matters: This highlights KAUST's role in developing Saudi talent for the energy sector and fostering collaboration between academia and industry.
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.
KAUST Ph.D. student Hanan Mohammed and postdoctoral fellow Yizhou Zhang presented their research at the Falling Walls Conference in Berlin. Zhang presented a novel MXene-hydrogel composite with biosensing applications, while Mohammed discussed 3D data storage architectures to reduce data center energy consumption. They were selected after winning the KAUST Falling Walls Lab in September. Why it matters: Showcasing KAUST researchers' work on an international stage highlights the university's contributions to materials science and sustainable computing.
This paper presents a UI-level evaluation of ALLaM-34B, an Arabic-centric LLM developed by SDAIA and deployed in the HUMAIN Chat service. The evaluation used a prompt pack spanning various Arabic dialects, code-switching, reasoning, and safety, with outputs scored by frontier LLM judges. Results indicate strong performance in generation, code-switching, MSA handling, reasoning, and improved dialect fidelity, positioning ALLaM-34B as a robust Arabic LLM suitable for real-world use.