KAUST has launched the Future Cement Initiative (FCI) in partnership with the Ministry of Industries and Mineral Resources and the National Committee of Cement Companies. The FCI aims to improve the economic and environmental competitiveness of cement manufacturing in Saudi Arabia through technology development. The initiative will focus on research into manufacturing technologies, emission reduction, and effective strategies for cement manufacturing. Why it matters: The FCI can position Saudi Arabia as a leader in the Middle East's cement industry while diversifying its economy and addressing environmental challenges.
KAUST hosted the Future Cement Initiative (FCI) National Workshop, gathering over 200 experts to advance low-carbon cement production in Saudi Arabia. Researchers presented findings on using locally sourced clay as sustainable cement blends, reducing the need for carbon-intensive clinker. The workshop addressed cement decarbonization, circular economy models, and the role of AI in sustainable construction. Why it matters: This initiative supports Saudi Arabia's sustainability goals by modernizing cement manufacturing and leveraging regional resources to reduce carbon emissions in the construction sector.
KAUST Professors William Roberts and Robert Dibble were inducted as Fellows of The Combustion Institute (CI) in February. Roberts was recognized for his work on laminar flames, turbulent combustion, and soot formation at elevated pressures. Dibble was inducted for exceptional contributions to developing and using laser diagnostics for combustion research. Why it matters: This recognition highlights KAUST's contributions to combustion research and strengthens its position as a leading institution in the field, attracting top students and researchers.
This paper introduces a novel fuzzy clustering method for circular time series based on a new dependence measure that considers circular arcs. The algorithm groups series generated from similar stochastic processes and demonstrates computational efficiency. The method is applied to time series of wind direction in Saudi Arabia, showcasing its practical potential.
A new benchmark, LongShOTBench, is introduced for evaluating multimodal reasoning and tool use in long videos, featuring open-ended questions and diagnostic rubrics. The benchmark addresses the limitations of existing datasets by combining temporal length and multimodal richness, using human-validated samples. LongShOTAgent, an agentic system, is also presented for analyzing long videos, with both the benchmark and agent demonstrating the challenges faced by state-of-the-art MLLMs.