KAUST Professor of Computer Science Peter Richtárik and his former student Nicolas Loizou, currently a postdoctoral researcher at Mila - Quebec Artificial Intelligence Institute and soon to take up an assistant professorship position at Johns Hopkins University, recently received the 2020 Computational Optimization and Applications (COAP) Best Paper Award.
Laurent Condat, a research scientist based in the KAUST Visual Computing Center, has recently been appointed as an Associate Editor of IEEE Transactions on Signal Processing (TSP). The peer-reviewed journal covers novel theory, algorithms, performance analyses, and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals.
KAUST Ph.D. student Dmitry Kovalev has been named one of nine recipients of the 2020 Ilya Segalovich Scientific Prize for Young Researchers. Awarded by the Russian multinational corporation Yandex, Dmitry received the accolade for his “significant advances in computer science.”

Together with our partners from Tsinghua University and Nanographics, our group has succeeded in depicting the first 3D visualizations of Cryo-EM microscopy tomography directly from the data. We are advancing the technology to allow for clear, noise-free visualization of this challenging data modality.

Researchers from the KAUST High-Performance Visualization Group (VCCVIS) have won the IEEE Scientific Visualization (SciVis) 2020 Best Paper Award at the IEEE Visualization Conference (IEEE VIS) 2020. Held virtually from October 25-30, IEEE VIS 2020 brought together a host of researchers and practitioners from academia, government, and industry to discuss advances in theory, methods and visual analytics applications.
Bernard Ghanem, KAUST associate professor of electrical and computer engineering and computer science, recently received the 2020 Abdul Hameed Shoman Award for Arab Researchers for ''Machine Learning and Big Data.''
A KAUST-designed symbolic algorithm to solve nonlinear ordinary differential equations (ODEs) has been selected for inclusion in the current version of the computer algebra system (CAS) Maple 2020. The global symbolic and numeric computing software system—developed by the Canadian company Waterloo Maple (Maplesoft)—is widely used by scientists, engineers, and researchers to analyze, visualize, and solve mathematical problems.