Dr. Mohamed Ferrag, a Lead Researcher at AIDRC, received the "Algeria Scopus Award" from Algeria's Ministry of Education and Higher Research for his contributions to computer science. Dr. Ferrag is an IEEE Senior Member and has authored many scientific papers and books. He was also ranked among the World's Top 2% Scientists from Stanford University in 2020-2022. Why it matters: This award recognizes and encourages scientific research and talent within the Algerian AI and computer science community.
KAUST Professor Mohamed Eddaoudi has won the 2023 Kuwait Prize in chemistry for his work on functional solid-state materials, specifically metal-organic frameworks (MOFs). His research focuses on innovative design strategies for these materials and their applications in gas separations, catalysis, energy storage, and carbon capture. Eddaoudi, a founding faculty member at KAUST since 2009, shares the prize with Prof. Nashaat Nassar from the University of Calgary. Why it matters: The award recognizes KAUST's research excellence and highlights the importance of materials science for energy and environmental sustainability within the Arab world.
The provided article discusses Mohamed Salah's potential departure from Liverpool at the end of the football season and his message to fans. This content is unrelated to artificial intelligence, machine learning, or Middle East AI news. Why it matters: This news falls outside the scope of AI research and industry developments in the Middle East.
The QU-NLP team presented their approach to the QIAS 2025 shared task on Islamic Inheritance Reasoning, fine-tuning the Fanar-1-9B model using LoRA and integrating it into a RAG pipeline. Their system achieved an accuracy of 0.858 on the final test, outperforming models like GPT 4.5, LLaMA, and Mistral in zero-shot settings. The system particularly excelled in advanced reasoning, achieving 97.6% accuracy. Why it matters: This demonstrates the effectiveness of domain-specific fine-tuning and retrieval augmentation for Arabic LLMs in complex reasoning tasks, even surpassing frontier models.
KAUST Professor Mohamed Eddaoudi is researching MOFs (metal-organic frameworks). MOFs have applications for clean energy. Why it matters: This research contributes to KAUST's and Saudi Arabia's broader clean energy and sustainability initiatives.
KAUST Ph.D. student Mohammed Aljahdali received the Best Paper award at the International Conference on Federated Learning Technologies and Applications (FLTA) 2025 for his research on federated learning. His paper, "Flashback: Understanding and Mitigating Forgetting in Federated Learning," introduces an algorithm to help AI systems retain knowledge across diverse datasets while preserving privacy. Aljahdali's research, supervised by Professor Marco Canini, focuses on training machine learning models directly on user devices. Why it matters: This award recognizes the growing talent and impactful research emerging from Saudi universities in the field of privacy-preserving AI.