KAUST ·
Xiaohang Li has joined the Computer, Electrical and Mathematical Science and Engineering Division at KAUST as an assistant professor of electrical engineering. He will focus on research and teaching within the electrical engineering domain. Why it matters: The appointment strengthens KAUST's faculty expertise in electrical engineering and related areas.
KAUST ·
KAUST Assistant Professor Xiaohang Li has won the 2018 Harold M. Manasevit Young Investigator Award for his work in metal-organic chemical vapor deposition (MOCVD) growth of semiconductors. Li will receive the award at the 19th International Conference on Metalorganic Vapor Phase Epitaxy in Japan. The award recognizes Li's contributions to deep UV lasers, B-III-N alloys, III-oxides, and blue and green emitters. Why it matters: This award highlights KAUST's growing prominence in advanced semiconductor research and its potential impact on the optoelectronics industry.
KAUST ·
KAUST and KACST co-organized the KSA Future of Semiconductors Forum in Riyadh to explore strategies for developing a semiconductor industry in Saudi Arabia. Participants discussed the critical need to secure the global supply chain for semiconductors, especially with rising demand from AI and other fields. KAUST faculty member Dr. Xiaohang Li noted that local semiconductor researchers and developers can play a key role in diversifying the Saudi economy. Why it matters: Developing a domestic semiconductor industry would support Saudi Arabia's ambitions in AI and other technology sectors while enhancing economic diversification and national security.
KAUST ·
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.
KAUST ·
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.
MBZUAI ·
MBZUAI welcomes Hao Li, CEO of Pinscreen, as a new faculty member specializing in virtual humans. Li envisions a future where virtual humans facilitate interactions and overcome limitations of physical presence, citing benefits like improved education and remote collaboration. His work focuses on the intersection of computer vision, computer graphics, and machine learning to enable immersive digital experiences. Why it matters: This signals MBZUAI's commitment to advancing research in virtual reality and the metaverse, potentially positioning the UAE as a leader in this emerging field.
KAUST ·
KAUST researchers demonstrated a new flash memory device design using gallium oxide, which can withstand harsh environments. In collaboration with the University of Michigan, KAUST researchers explained a key molecular event for the activation of an enzyme associated with cancer. The Summer 2023 issue of KAUST Discovery is now available. Why it matters: These research achievements highlight KAUST's contributions to advanced materials science and biomedical research, with potential applications in space technology and cancer treatment.
KAUST ·
KAUST Associate Professor Xiangliang Zhang is using machine learning to analyze social media posts on Twitter related to COVID-19. Her team at KAUST's Computational Bioscience Research Center is analyzing sentiment in tweets using hashtags like #coronavirus and #covid19. Zhang aims to use this data to help predict localized outbreaks and provide an early warning system for governments and organizations. Why it matters: This research demonstrates the potential of AI-powered sentiment analysis to support public health efforts and inform decision-making during pandemics in the Middle East and globally.