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 doctoral students Xiujuan Zhang and Aftab Hussain, along with Research Scientist Dr. Alberto Casu, will attend the 66th Lindau Nobel Laureate Meeting. The three scientists were selected based on their work at KAUST. Why it matters: This highlights KAUST's commitment to fostering scientific talent and contributing to global research.
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.
Xiuying Chen from KAUST presented her work on improving the trustworthiness of AI-generated text, focusing on accuracy and robustness. Her research analyzes causes of hallucination in language models related to semantic understanding and neglect of input knowledge, and proposes solutions. She also demonstrated vulnerabilities of language models to noise and enhances robustness using augmentation techniques. Why it matters: Improving the reliability of AI-generated text is crucial for its deployment in sensitive domains like healthcare and scientific discovery, where accuracy is paramount.
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.
KAUST alumnus Marie-Jean Thoraval was selected for Xi'an Jiaotong University’s “10 Young Scholars of Distinction” award, the first foreign teacher to receive this honor. Thoraval's current research focuses on the dynamics of interfacial flows, combining high-speed imaging with numerical simulations. He developed research facilities at Xi'an Jiaotong University to study drops' and bubbles' dynamics. Why it matters: This award highlights KAUST's role in producing impactful researchers and fostering international collaboration in science and engineering.
KAUST signed strategic cooperation agreements with leading business and academic institutes in Shenzhen, China, including the Research Institute of Tsinghua University and Shenzhen Innox Academy. The agreements aim to accelerate knowledge exchange and commercialize technologies. Objectives include industrial innovation, tech transfer, talent sharing, and joint R&D. Why it matters: The partnerships aim to leverage China's innovation ecosystem to help KAUST develop market-ready products and address global challenges.
KAUST Professor Xixiang Zhang was elected as a fellow of the American Physical Society (APS) in September. Zhang is a professor of Material Science and Engineering. The fellowship recognizes his contributions to the field of physics. Why it matters: Recognition of KAUST faculty highlights the institution's growing prominence in international scientific communities.