KAUST hosted representatives from Islamic Development Bank (IsDB) member countries to showcase its aquaculture expertise. The IsDB funded the visit, with co-investment from Innovative Contractors for Advanced Dimensions (ICAD), to introduce KAUST's aquaculture technology to representatives from Morocco, Mali, Burkina Faso and Egypt. The visit aimed to accelerate aquaculture capabilities in North and West Africa, with ICAD pledging up to $20 million in grants for future projects using KAUST technology. Why it matters: This collaboration demonstrates KAUST's role as a regional hub for advanced aquaculture technology and promotes sustainable food production in IsDB member countries.
The Symposium on Data Mining and Applications (SDMA 2014) was organized by MEGDAM to foster collaboration among data mining and machine learning researchers in Saudi Arabia, GCC countries, and the Middle East. The symposium covered areas such as statistics, computational intelligence, pattern recognition, databases, Big Data Mining and visualization. Acceptance was based on originality, significance and quality of contribution.
This paper introduces a unified deep autoregressive model (UAE) for cardinality estimation that learns joint data distributions from both data and query workloads. It uses differentiable progressive sampling with the Gumbel-Softmax trick to incorporate supervised query information into the deep autoregressive model. Experiments show UAE achieves better accuracy and efficiency compared to state-of-the-art methods.
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.
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Munther Dahleh from MIT gave a talk on information design under uncertainty, focusing on the challenges of creating an information marketplace. The talk addressed the externality faced by firms when information is allocated to competitors, and considered two models for this externality. The presentation included mechanisms for both models and highlighted the impact of competition on the revenue collected by the seller. Why it matters: The research advances understanding of information markets and mechanism design, relevant to the growing data economy in the GCC region.
KAUST highlights postdoctoral fellows Yi Jin Liew, Isabelle Schulz, Maren Ziegler and Neus Garcias Bonet outside the University Library. The article mentions King Abdullah bin Abdulaziz Al Saud (1924 – 2015). It encourages applications to KAUST's Discovery Postdoctoral program. Why it matters: This brief announcement signals KAUST's ongoing investment in attracting international research talent to Saudi Arabia.
KAUST researchers are developing iSCAN, a rapid, field-deployable COVID-19 test using RT-LAMP coupled with CRISPR-Cas12. The iSCAN system is designed for rapid, specific detection of SARS-CoV-2 and can be deployed by untrained personnel. The researchers are benchmarking iSCAN against commercial kits and seeking emergency use authorization from the Saudi FDA. Why it matters: A rapid, accurate, and field-deployable COVID-19 test could significantly improve pandemic management and control in Saudi Arabia and beyond.