Five young researchers from KAUST participated in the virtual 70th Lindau Nobel Laureate Meeting, which focused on interdisciplinarity. The KAUST participants included Ph.D. students, postdocs, and faculty member Nazek El-Atab. El-Atab's research focuses on smart memory and electronic devices, with applications in computing and sensing. Why it matters: KAUST's representation at this prestigious event highlights the university's commitment to fostering scientific collaboration and innovation among its researchers.
KAUST is highlighted for its commitment to multidisciplinary research, innovation, and strong leadership, particularly regarding women's education. The university was the first mixed-gender university in Saudi Arabia, with women comprising around 40% of its student population. KAUST actively recruits female faculty members and appoints them to leadership positions, demonstrated through workshops like Women in Science and Engineering (WISE). Why it matters: This underscores the increasing role of women in STEM fields within Saudi Arabia, facilitated by institutions like KAUST.
KAUST professor Niveen Khashab was named the first Great Arab Mind in natural sciences. The Great Arab Minds award was conceived by Sheikh Mohammed Bin Rashid al Maktoum to recognize Arabs for achievements in science, architecture, engineering, economics, literature, and medicine. Khashab, an organic chemist, was selected for contributions to nanomaterials development, synthesis, and application in medicine, industry, and agriculture. Why it matters: The award highlights KAUST's role in fostering scientific talent and contributing to advancements in nanotechnology and related fields within the Arab world.
The paper introduces ADAB (Arabic Politeness Dataset), a new annotated Arabic dataset for politeness detection collected from online platforms. The dataset covers Modern Standard Arabic and multiple dialects (Gulf, Egyptian, Levantine, and Maghrebi). It contains 10,000 samples across 16 politeness categories and achieves substantial inter-annotator agreement (kappa = 0.703). Why it matters: This dataset addresses the under-explored area of Arabic-language resources for politeness detection, which is crucial for culturally-aware NLP systems.
KAUST Discovery Associate Professor of Chemical Science Niveen Khashab received a 2017 L’Oréal-UNESCO For Women in Science Award. The award recognizes her research contributions in the field of physical science, specifically organic chemistry. The award highlights the impact of KAUST researchers on the global scientific community. Why it matters: This recognition underscores the growing prominence of women in STEM fields within the Middle East and the increasing global impact of research originating from Saudi Arabia.
Dalal Alezi, a Ph.D. student in KAUST's Physical Science and Engineering Division, has received the inaugural PSE Division Student Award. Alezi is a fourth-year Ph.D. candidate. The award recognizes outstanding Ph.D. candidates within the division. Why it matters: The award highlights KAUST's commitment to recognizing and supporting exceptional talent in science and engineering.
The authors introduce Nile-Chat, a collection of LLMs (4B, 3x4B-A6B, and 12B) specifically for the Egyptian dialect, capable of understanding and generating text in both Arabic and Latin scripts. A novel language adaptation approach using the Branch-Train-MiX strategy is used to merge script-specialized experts into a single MoE model. Nile-Chat models outperform multilingual and Arabic LLMs like LLaMa, Jais, and ALLaM on newly introduced Egyptian benchmarks, with the 12B model achieving a 14.4% performance gain over Qwen2.5-14B-Instruct on Latin-script benchmarks; all resources are publicly available. Why it matters: This work addresses the overlooked aspect of adapting LLMs to dual-script languages, providing a methodology for creating more inclusive and representative language models in the Arabic-speaking world.