KAUST Professor Marc Genton and his former postdoc Stefano Castruccio jointly won the 2017 Wilcoxon Award for their paper in Technometrics. Their paper, "Compressing an ensemble with statistical models: An algorithm for global 3D spatio-temporal temperature," details a data-compression scheme for climate simulations. The method reduces data-storage requirements and accelerates climate research capacity. Why it matters: This award highlights KAUST's contribution to statistical methods for climate modeling and big data analysis, particularly relevant for studying renewable energy resources in Saudi Arabia.
KAUST Ph.D. student Yuxiao Li received a Student Paper Award from the American Statistical Association (ASA) for his paper on efficient estimation of non-stationary spatial covariance functions. The award-winning paper is Li's first research paper at KAUST, completed as a member of the Environmental Statistics Group led by Professor Ying Sun. His research focuses on short-term space-time precipitation modeling, addressing the challenges of modeling rainfall zeros and amounts along with complex spatio-temporal dependencies. Why it matters: This award recognizes KAUST's contributions to advanced statistical methods for environmental modeling, highlighting the university's strength in addressing complex environmental challenges.
Mae AlMansoori from TII's Directed Energy Research Center won the Young Scientist Award at URSI Kleinheubacher Tagung 2020. Her paper introduced a correlation metric to evaluate the influence of random variables on high-power electromagnetic sources, specifically a Vircator model. The study combined extreme value theory and descriptive statistics to analyze peak output power variability and identify dominant factors. Why it matters: The research offers a framework for managing uncertainties in high-power electromagnetic sources and optimizing their efficiency, relevant for defense and energy applications in the region.
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.
KAUST Ph.D. alumna Sabrina Vettori and Ph.D. student Yuxiao Li received a Distinguished Student Paper Award at the 2018 Eastern North American Region (ENAR) Spring Meeting of the International Biometric Society. Li's paper focused on efficient estimation for non-stationary spatial covariance functions, while Vettori's paper addressed Bayesian hierarchical modelling of air pollution extremes. Both students were recognized for their contributions to statistical environmental studies and air pollution modeling. Why it matters: This award highlights KAUST's commitment to fostering high-quality research and recognizes the achievements of its students in addressing critical environmental challenges.
KAUST Professors Mohamed Eddaoudi and Omar Knio have received the Abdul Hameed Shoman Award for Arab Researchers. Eddaoudi was recognized for his work on metal-organic frameworks (MOFs) for clean energy and carbon capture, while Knio was honored for his contributions to mathematical modeling and simulation of thermo-fluid systems. The award, established in 1982, recognizes outstanding scientific output and aims to encourage a culture of scientific research in the Arab world. Why it matters: This recognition highlights the impactful research being conducted at KAUST and underscores the importance of Arab researchers' contributions to solving regional and global challenges.
KAUST Ph.D. student Michał Mańkowski won a Poster of Distinction Award at the American Society of Transplant Surgeons (ASTS) 18th Annual State of the Art Winter Symposium for his work on kidney allocation systems. His poster described a simulation for a new kidney allocation system to accelerate organ placement, focusing on marginal quality kidneys. The research involves combinatorial optimization, operation research and management science with healthcare applications, stemming from a collaboration with Johns Hopkins School of Medicine. Why it matters: The research aims to improve organ transplantation efficiency and save lives by optimizing kidney allocation systems, demonstrating the potential of AI and optimization techniques in healthcare.
KAUST Ph.D. student Gaurav Agarwal won the best student paper award at the International Indian Statistical Association's 2019 Student Paper Competition for his work on the joint distribution of wind speed and direction. Agarwal's research involved developing a visualization tool for bivariate functional data, which can be used in climate and weather prediction models. He also received a scholarship based on his contributions using R. Why it matters: This award recognizes innovative work in environmental statistics at KAUST, highlighting the university's contributions to data science and statistical learning with applications to climate modeling.