KAUST Associate Professor Xiangliang Zhang leads the Machine Intelligence and Knowledge Engineering (MINE) group, focusing on machine learning and data mining algorithms for AI applications. The MINE group researches complex graph data to profile nodes, predict links, detect computing communities, and understand their connections. Zhang's team also works on graph alignment and recommender systems. Why it matters: This research contributes to advancing machine learning techniques at a leading GCC institution, potentially impacting various AI applications in the region.
KAUST Associate Professor Xiangliang Zhang presented her work on mining streaming and temporal data at the International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI-18) in Stockholm. Her talk, "Mining Streaming and Temporal Data: from Representation to Knowledge," summarized her research on mining data streams. Zhang directs the KAUST Machine Intelligence and kNowledge Engineering (MINE) group, which focuses on knowledge discovery from large-scale data. Why it matters: Showcases KAUST's contributions to AI research and highlights the university's growing recognition within the international AI community.
Ma’aden has joined the KAUST Industry Collaboration Program (KICP) as a strategic partner. This agreement provides Ma'aden access to KAUST's research, technologies, and talent pool. The partnership aims to address industrial challenges such as water scarcity, sustainability, and energy efficiency in remote areas across the Kingdom. Why it matters: This collaboration can drive innovation in the Saudi mining industry by leveraging KAUST's research capabilities to develop solutions tailored to the region's specific challenges.
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.
KAUST and the Ministry of Industry and Mineral Resources in Saudi Arabia have signed an agreement to launch three specialized academic programs focused on industry and mining. These programs include undergraduate, master's, and doctoral studies, with the aim of developing human capital and fostering innovation in these sectors. The MoU also plans to facilitate the admission of Saudi talents to global universities via scholarships. Why it matters: This partnership aims to align KAUST's research and education with the needs of Saudi Arabia's industrial and mining sectors, supporting the Kingdom's Vision 2030 goals for economic diversification and technological advancement.
KAUST hosted the KAUST Research Conference: Advances in Well Construction with Focus on Near-Wellbore Physics and Chemistry from November 7 to 9. The conference was co-chaired by Eric van Oort, a professor at UT Austin, and Tadeusz Patzek, director of the University’s Upstream Petroleum Engineering Research Center. Attendees included professors from the University of Queensland and UT Austin, and directors from GenesisRTS and Labyrinth Consulting Services, Inc. Why it matters: The conference facilitates international collaboration on advancements in petroleum engineering and well construction technologies, which are strategically important for Saudi Arabia.
Conor McMenamin from Universitat Pompeu Fabra presented a seminar on State Machine Replication (SMR) without honest participants. The talk covered the limitations of current SMR protocols and introduced the ByRa model, a framework for player characterization free of honest participants. He then described FAIRSICAL, a sandbox SMR protocol, and discussed how the ideas could be extended to real-world protocols, with a focus on blockchains and cryptocurrencies. Why it matters: This research on SMR protocols and their incentive compatibility could lead to more robust and secure blockchain technologies in the region.
The UAE's Ministry of Energy and Infrastructure (MoEI) and the Technology Innovation Institute (TII) have partnered to create 3D maps of the UAE's mineral and renewable resources. TII's Directed Energy Research Center (DERC) will support MoEI in this effort, contributing its expertise to identify resources like geothermal energy and analyze geological data. The collaboration aims to support the UAE's Net Zero 2050 Strategy by enabling the exploration and utilization of undiscovered renewable and mineral resources. Why it matters: This initiative leverages local expertise to map domestic resources, aligning technological advancement with sustainability goals for the UAE.