Congratulations to Computer Science alumna Imane Boudellioua (Ph.D. ’19, MS ’12) for receiving a prize in the 19th edition of the annual KACST Almarai National Prize for Creative Scientific Work for Students (Ph.D. Level). As a Ph.D. student in the Computational Bioscience Research Center, Dr. Boudellioua worked in machine learning and data mining algorithms, with research targeting the potential to help patients with mysterious ailments find genetic causes for their undiagnosed disease.
Runar Reve, a former KAUST Visiting Student Research Program (VSRP) student, recently received the International Society for Computational Biology’s (ISCB) Bio-Ontologies COSI – Best Talk Award at the 28th Conference on Intelligent Systems for Molecular Biology (ISMB) 2020.
A likeness between genes of the SARS and COVID-19 viruses could inform research into potential treatments.
KAUST faculty member Robert Hoehndorf was recently promoted from the rank of assistant professor to associate professor. Hoehndorf’s promotion caps a year-long process where the German researcher’s scientific and scholarly output was measured and evaluated by internal and external reviews.
Fernando is a 23-year-old Information Technology graduate fromYachay Tech University in Urcuquí, Ecuador. He has planned to continue his academic career at KAUST under the supervision of Professor Robert Hoehndorf.
A method for finding genes that spur tumor growth takes advantage of machine learning algorithms to sift through reams of molecular data collected from studies of cancer cell lines, mouse models and human patients.
Abeer Almutairi, a student under the supervision of Professor Robert Hoehndorf, defended her Master's thesis "Unsupervised Method for Disease Named Entity Recognition" on November 4, 2019.
Mona Alshahrani a Ph.D. candidate under the supervision of Professor Robert Hoehndorf Defended her Ph.D. thesis "Knowledge Graph Representation Learning: Approaches and Applications in Biomedicine."
Bridging the knowledge gap in artificial intelligence requires an embedding function that helps step between different types of "thinking."