KAUST President Tony F. Chan has been awarded the 2020 SIAM Prize for Distinguished Service to the Profession. The award recognizes Chan's contributions to applied and computational mathematics, imaging science, and scientific computing. Chan has served on advisory boards for KAIST, SUSTech, and the University of Vienna, and is a member of the NEOM Higher Council. Why it matters: The recognition highlights KAUST's leadership and influence in advancing mathematical sciences and its applications on a global stage.
KAUST Ph.D. student Chiheb Ben Hammouda won the best poster award at the Society for Industrial and Applied Mathematics Conference on Financial Mathematics & Engineering (FM19) for his work on option pricing under the rough Bergomi model. The winning poster, titled "Hierarchical adaptive sparse grids and quasi-Monte Carlo for option pricing under the rough Bergomi model," details research carried out under the supervision of KAUST Professor Raul Tempone. The research group designed new efficient numerical methods for pricing derivatives under the rough Bergomi model by combining smoothing techniques. Why it matters: This award highlights KAUST's growing expertise in financial mathematics and its contribution to solving complex problems in the field using advanced numerical methods.
KAUST's Stochastic Numerics Research Group is developing methods for pricing European options. Their approach, detailed in an upcoming Journal of Computational Finance article, focuses on systematically tuning parameters to achieve accuracy while minimizing computational effort. The goal is to enable automated computation of fair prices for options contracts, similar to how insurance companies determine premiums. Why it matters: This research advances computational finance in the region, potentially improving risk management and investment strategies.
KAUST has been awarded the ACM Gordon Bell Prize for Climate Modelling, considered the "Nobel" of high-performance computing, for their work on exascale climate emulators. The winning paper, a collaborative effort with institutions including the NSF National Center for Atmospheric Research, addresses the computational and storage demands of high-resolution earth system models. The KAUST team included Sameh Abdulah, Marc G. Genton, David E. Keyes, and others. Why it matters: This is the first time an institution in the Middle East has won the prize, highlighting KAUST's leadership in high-performance computing and climate research in the region.
KAUST researchers have been selected as finalists for two ACM Gordon Bell Prizes for high-performance computing. One project used NVIDIA GPUs to enhance genetic studies from the UK Biobank, achieving 133x speedup over existing software. The other developed an exascale climate emulator with higher spatial-temporal resolution than current models, demonstrated on supercomputers like Shaheen III. Why it matters: The recognition highlights KAUST's strength in high-performance computing research and its contributions to both genetic analysis and climate modeling.
KAUST Ph.D. students David Evangelista and Xianjin Yang won best paper awards at international conferences this summer for their work in mean-field game theory. Evangelista's paper focused on solutions for stationary mean-field games with congestion, while Yang's paper developed numerical methods for homogenization problems. The awards were presented at the 18th International Symposium on Dynamic Games and Applications in France and the 12th American Institute of Mathematical Sciences (AIMS) Conference in Taiwan. Why it matters: The recognition highlights KAUST's strength in applied mathematics and computational science, specifically in the emerging field of mean-field games with applications across various domains.
KAUST Ph.D. student Jian Cao received a best paper award from the American Statistical Association (ASA) for his paper on computing high-dimensional normal and Student-t probabilities. The paper uses Tile-Low-Rank Quasi-Monte Carlo and Block Reordering. Cao, a member of Professor Marc Genton's group, will be recognized at the ASA's Joint Statistical Meetings. Why it matters: This award highlights KAUST's strength in high-performance computing and statistical research, contributing to advancements in handling complex, high-dimensional datasets.
Marcus Engsig from DERC will present a paper at the MATLAB User Group Meeting in Abu Dhabi on October 6. The paper, titled ‘Generalization of Higher Order Methods For Fast Iterative Matrix Inversion Compatible With GPU Acceleration’, discusses a novel approach to matrix inversion using GPUs. The method, named Nested Neumann, achieves 4-100x acceleration compared to standard MATLAB methods for large matrices. Why it matters: This research contributes to faster computation in numerical and physical modeling, crucial for processing large datasets in various scientific and engineering applications in the region.