Marcus Engsig at DERC has developed DomiRank, a new centrality metric to quantify the dominance of nodes within networks. DomiRank integrates local and global topological information to determine the importance of each node for network stability. The research demonstrates that nodes with high DomiRank values indicate vulnerable areas heavily dependent on dominant nodes. Why it matters: This metric can help identify critical infrastructure components and vulnerabilities in complex systems, enhancing resilience against targeted attacks.
KAUST was ranked first in the Times Higher Education (THE) Arab University Rankings 2023, improving from second place the previous year. KAUST achieved a perfect score of 100 for research environment and saw improvements in industry income and international outlook. KAUST's supercomputer Shaheen III was also ranked the most powerful in the Middle East and #20 globally. Why it matters: This ranking highlights the increasing strength of Saudi Arabian universities and the region's growing focus on research, development, and innovation, especially in areas like AI.
MBZUAI is now ranked 24th globally in AI, computer vision, machine learning, and natural language processing, according to CSRankings. This ranking is attributed to the addition of faculty like Preslav Nakov, Hanan Al Darmaki, and Samuel Horvath. MBZUAI now ranks ahead of universities like the University of Michigan and Imperial College London in specific AI fields. Why it matters: This ranking establishes MBZUAI as the top CS institution in the Arab World and highlights the UAE's growing prominence in AI research.
KAUST was ranked 119th among 500 global academic institutions in the Nature Index 2020, securing the top position in Saudi Arabia with 84% of the Kingdom's fractional count share. The university also achieved notable rankings in specific disciplines, including 69th in physical sciences, 87th in chemistry, and 89th in earth and environmental sciences. KAUST's Nature Index FC output surpasses that of 17 countries, including the UAE. Why it matters: This ranking highlights KAUST's strong research output and its increasing contribution to global scientific advancements, strengthening the Kingdom's position in research and innovation.
KAUST has been ranked sixth globally and first in the MENA region in the Nature Young Universities Index, which lists the top 175 universities established in the last 50 years. The ranking is based on fractional count of articles published in 2018 in 82 high-quality natural science journals. The report praised KAUST's research quality and contribution to total research outputs in the Middle East. Why it matters: This ranking highlights the rapid rise of KAUST as a leading research institution in the region and globally, demonstrating Saudi Arabia's commitment to scientific advancement.
KAUST's nanoscience and nanotechnology program was ranked 18th globally in the 2022 US News & World Report's Best Global Universities list. The ranking reflects KAUST's strong performance in basic and applied research at the micro and nano levels, spanning disciplines from chemistry to medical science. KAUST scored 81.7 out of 100, with high scores in citations, normalized citation impact, and international collaboration. Why it matters: This ranking highlights the growing prominence of Middle Eastern universities in advanced scientific fields and KAUST's contributions to global nanoscience research.
KAUST was ranked first in Saudi Arabia and in the global top twenty in the Nature Index Annual Tables' new normalized ranking. The ranking considers the number of high-quality articles published as a proportion of an institute's overall output in the natural sciences. This normalized ranking allows institutions of different sizes to be compared on the same basis. Why it matters: This ranking highlights KAUST's growing impact on global scientific research and its commitment to producing high-quality publications.
KAUST researchers from statistics and earth science collaborated to improve earthquake source modeling. They developed a statistical ranking tool to classify 2D fields, applicable to geoscience models like temperature or precipitation. The tool helps compare different 2D fields describing the earthquake source process and quantify inter-event variability. Why it matters: This cross-disciplinary approach enhances the reliability of earthquake rupture models, contributing to better hazard assessment and risk management in seismically active regions.