An international team of scientists, including KAUST high performance computing experts and astronomers from the Paris Observatory and the National Astronomical Observatory of Japan (NAOJ), in collaboration with NVIDIA, is taking the search for habitable planets and observation of first epoch galaxies to the next level.
Representatives from the KAUST Computational Bioscience Research Center (CBRC), King Abdulaziz City for Science and Technology (KACST), King Saud University (KSU), Taibah University, National Guard Health Affairs (NGHA) and the Saudi Arabia Ministry of Health (MOH) met on October 1 to iron out details of a national initiative to fight infectious diseases.
The European Conference on Computational Biology (ECCB) is one of the most important conferences in the field of bioinformatics and computational biology.  Held in a different European city annually, this year's conference will take place in the historic city of Athens, Greece on September 8-12, 2018.  
The recent KAUST Research Conference: Computational and Statistical Interface to Big Data brought together leading computer science researchers and statistical experts to discuss the current state and future of data science. Held on campus from March 19 to 21, the conference covered such data science topics as succinct data representation and storage; big data visualization; parallel and distributed algorithms for inference and optimization; and analysis of large graphs and networks.
Sarah Alghamdi successfully defended her master's thesis on April 10, 2018. Her project, entitled "Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Ageing and Longevity in Inbred Mouse Strains", was well-received by a panel of professors that included Professor Vladimir Bajic, Associate Professor Xin Gao and Assistant Professor Robert Hoehndorf.
​The student will work on combining methods from Symbolic Artificial Intelligence (formal logics, rule-based systems) with machine learning and statistical approaches to data mining, and apply these methods to biomedical datasets. Major application areas include understanding molecular mechanisms underlying traits, phenotypes, and disease, and identifying ways to perturb biological systems through bioactive compounds (drugs).​