KAUST professor David Ketcheson uses mathematical modeling to understand COVID-19 transmission. He applies differential equations to explain the progression of SARS-CoV-2, utilizing the SIR model to predict the spread. Ketcheson's analysis suggests that the reproduction number for COVID-19 could be as high as 5, emphasizing the need for social distancing. Why it matters: This highlights the role of mathematical modeling and data analysis in understanding and predicting the spread of infectious diseases, particularly in the context of pandemic response.
KAUST Professor Peter Markowich has been named a 2022 Fellow of the American Mathematical Society (AMS). He is recognized for contributions to partial differential equations, particularly the mathematical and numerical analysis of dispersive equations. Markowich applies differential mathematics to disciplines such as physics, AI, biology and engineering, including research on leaf venation patterns. Why it matters: This recognition highlights KAUST's strength in applied mathematics and its faculty's contributions to both theoretical and interdisciplinary research.
KAUST Professor of Applied Mathematics and Computational Science, Dr. Peter Markowich, has been named a 2020 Fellow to the European Academy of Sciences. This recognizes his work in the mathematical and numerical analysis of partial differential equations. Markowich joined KAUST in 2011 and has contributed to over 270 projects worldwide. Why it matters: This honor brings recognition to KAUST's faculty and highlights the university's contribution to advanced mathematical research with applications across science and engineering.
KAUST hosted the Advances in Uncertainty Quantification Methods, Algorithms and Applications conference (UQAW2016) in January 2016. The event featured 75 presentations and 20 invited speakers from various countries. Professor Raul Tempone presented research on computational approaches to fouling accumulation and wear degradation using stochastic differential equations. Why it matters: This work provides a new computational approach based on stochastic differential equations to predict fouling patterns of heat exchangers which can optimize maintenance operations and reduce engine shut-down periods.
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 hosted the New Challenges in Heterogeneous Catalysis research conference from January 29-31. The conference brought together catalysis researchers from KAUST and abroad to inspire future research and discuss challenges in heterogeneous catalysis. Discussions focused on new chemistry, catalytic materials, understanding catalytic processes, and activation of small molecules like methane and carbon dioxide. Why it matters: Catalysis research is crucial for KAUST's research thrusts in food, water, energy, and environment, contributing to sustainable development and green chemistry in the region.
KAUST researchers are exploring novel chemical reactors and separation processes using mathematical design, with a focus on time and shape variables to enhance transport, heat transfer, and mass transfer. By aligning design, modeling, and 3D printing, they create customized shapes with great complexity and less material. This approach allows for the creation of bespoke reactors and separation processes tailored to specific applications, improving efficiency and reducing energy consumption. Why it matters: This research demonstrates the potential of advanced manufacturing techniques to revolutionize industrial design in the Middle East's chemical and pharmaceutical sectors.
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.