Lucidya, a startup founded by Saudi entrepreneurs including KAUST alumnus Zuhair Khayyat, utilizes AI and Big Data to analyze social media content from platforms like Twitter and Facebook, as well as articles from 200 million websites in over 120 languages. The technology predicts user emotions, detects interests, and provides content analyses to customers for better decision-making. Lucidya commercially transformed the scientific research 'Tagreed' to start their company. Why it matters: This demonstrates the growing potential of Saudi startups in leveraging AI for data analysis and social media monitoring, and it showcases the role of KAUST in fostering technological innovation and entrepreneurship within the Kingdom.
KAUST held a research conference on Computational and Statistical Interface to Big Data from March 19-21. The conference covered topics like data representation, visualization, parallel algorithms, and large-scale machine learning. Participants came from institutions including the American University of Sharjah, Aalborg University, and others to exchange ideas. Why it matters: The conference highlights KAUST's focus on promoting big data research and collaboration to address challenges and opportunities in various scientific fields within the Kingdom and globally.
KAUST's Computational Bioscience Research Center (CBRC) held a Research Conference on Big Data Analyses in Evolutionary Biology. The conference focused on the impact of large "omics" datasets on evolutionary biology, requiring big data approaches for analysis. Researchers discussed how computer science can contribute to biology and vice versa. Why it matters: Such interdisciplinary events at KAUST can foster innovation at the intersection of computational science and biology, advancing research in both fields.
Weizmann Institute Professor Eran Segal presented his work on the Human Phenotype Project at MBZUAI. The project is a large-scale biobank with data from over 10,000 participants, integrating medical history, lifestyle, and molecular profiling. Segal aims to use this data to develop personalized disease prevention and treatment plans. Why it matters: This research highlights the potential of interdisciplinary collaboration and big data analysis to advance personalized medicine in the region.
KAUST alumnus Faisal Nawab (M.S. '11) is now an assistant professor of computer science and engineering at UC Santa Cruz. His master's thesis at KAUST focused on building wireless network infrastructure, supervised by KAUST Associate Professor Basem Shihada. Nawab's current research involves developing systems for rapid data analysis in cloud computing and Big Data. Why it matters: This highlights KAUST's role in training researchers who are now contributing to advancements in computing and data analysis globally.