KAUST Professor Marc Genton has been selected as the 2020 Georges Matheron Lecturer of the International Association for Mathematical Geosciences. Genton will present a lecture at the 36th International Geological Congress in Delhi, India, focusing on geostatistics, climate model outputs, and the ExaGeoStat software developed at KAUST. His lecture will cover Matheron's theory of regionalized variables and showcase ExaGeoStat, a high-performance software for geostatistics with exascale computing capability developed at KAUST. Why it matters: This recognition highlights KAUST's contributions to advanced statistical methods and high-performance computing in geosciences, enhancing its international reputation in these fields.
This paper introduces a domain generalization (DG) method for Diabetic Retinopathy (DR) classification that maximizes mutual information using a large pretrained model. The method aims to address the challenge of domain shift in medical imaging caused by variations in data acquisition. Experiments on public datasets demonstrate that the proposed method outperforms state-of-the-art techniques, achieving a 5.25% improvement in average accuracy.
KAUST and the International Medical Center (IMC) have signed an MoU to collaborate on medical research related to wellness, quality of life, and population health management. The partnership aims to develop AI applications for diagnosis and treatment, along with research in precision medicine and advanced therapies. The collaboration aligns with Saudi Vision 2030's goals to build a sustainable, knowledge-driven healthcare future. Why it matters: This agreement signifies a push to integrate AI and precision medicine into practical medical solutions within the Saudi healthcare system.
KAUST held the Imaging and Active Tectonics of the Red Sea Region workshop, gathering over 20 international and 30 local researchers. The workshop aimed to improve understanding of seismicity, volcanism, and Earth structure in Saudi Arabia and the Red Sea region. Participants came from countries surrounding the Red Sea, as well as the US, UK, France, Brazil, and South Korea. Why it matters: The event fosters international collaboration and data exchange to better monitor and model seismic and volcanic activity in a geologically active region.
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.
AMRC researchers Jide Oyebanji and Tarcisio Silvia will present papers at the MATLAB User Group Meeting in Abu Dhabi. Oyebanji's paper focuses on the 'Design of an Interactive TPMS Designing Desktop App' using MATLAB's numerical capabilities. Silvia's presentation discusses the optimization of MIMO active vibration controllers for electromechanical systems using MATLAB Simulink and Particle Swarm Optimization. Why it matters: The presentations showcase the application of computational tools like MATLAB in advanced materials research and digital engineering within the UAE.
Researchers from the Directed Energy Research Center (DERC) will present research papers at the 17th Workshop of the International Lithosphere Program Task Force on Sedimentary Basins in Abu Dhabi. Dr. Meixia Geng's study identifies potential geothermal exploration sites in the UAE based on Curie isotherm depths. Dr. Felix Vega's research demonstrates drone-borne synthetic aperture radar (SAR) for subsurface mapping of underground cavities. Why it matters: These studies showcase the UAE's commitment to sustainable development through geothermal energy exploration and advanced subsurface imaging techniques.
Nicu Sebe from the University of Trento presented recent work on video generation, focusing on animating objects in a source image using external information like labels, driving videos, or text. He introduced a Learnable Game Engine (LGE) trained from monocular annotated videos, which maintains states of scenes, objects, and agents to render controllable viewpoints. Why it matters: This talk highlights advancements in cross-modal AI, potentially enabling new applications in gaming, simulation, and content creation within the region.