KAUST researchers have developed a new artificial intelligence model designed to improve the efficiency and accuracy of mineral exploration activities in Saudi Arabia. This model aims to identify promising geological sites for mineral deposits more effectively. The initiative supports Saudi Arabia's efforts to diversify its economy and enhance its mining sector capabilities. Why it matters: This development could significantly accelerate the discovery of new mineral resources, bolstering the Kingdom's economic diversification goals and positioning it as a leader in AI-driven natural resource management.
KAUST researchers have developed an AI system for the Saudi Geological Survey (SGS) to improve the scientific understanding of seismic activity in Saudi Arabia. The AI system helps the SGS analyze swarm earthquakes, which are common in volcanic regions and difficult to decipher using conventional methods. The system allows for a more reliable survey of seismic regions, better infrastructure planning, and improved building codes. Why it matters: The AI system enhances Saudi Arabia's ability to monitor and respond to seismic events, contributing to public safety and infrastructure resilience.
KAUST Ph.D. students Kai Lu and Yuqing Chen won Best Presentation awards at a Society of Exploration Geophysicists workshop in Beijing. Lu's research focuses on machine learning applications in seismic processing, while Chen uses machine learning for automated semblance spectrum picking. They both leverage KAUST's Shaheen II supercomputer for their work. Why it matters: This highlights the increasing role of AI and ML in the oil and gas industry, and KAUST's contribution to advancing these technologies.
KAUST researchers are using AI to analyze satellite imagery for the automated detection of ancient stone structures in northwest Saudi Arabia, including mustatils (rectangular structures dating to the late 6th millennium BCE) and ruins in circular and triangular shapes. They developed a deep learning algorithm trained on manually identified datasets to isolate similar features over a wide area. The tool converts detected pixels into geodetic coordinates using GPS, assembling them into an online map and database. Why it matters: This project exemplifies computational archaeology, speeding up archaeological discoveries, promoting cultural heritage, and providing a methodology useful to other sectors of the economy.
KAUST is developing AI-driven personalized learning and testing platforms to address STEM education resource gaps in Saudi Arabia. The project involves building an intelligent tutoring system in collaboration with Saudi high schools, the Ministry of Education, and SDAIA. The AI tutor, designed in a Socratic style, enhances learning through GenAI tutoring, including in Arabic, and supports teachers by generating test and homework problems. Why it matters: This initiative aims to prepare Saudi youth for future workforce demands and enhance educational outcomes, aligning with Saudi Vision 2030's goals for human capital development.