Dr. Paula Moraga is part of a multidisciplinary KAUST research team that applies models to COVID-19. She has worked on projects examining malaria in Africa and leptospirosis in Brazil, and the models she develops rely on in-depth knowledge about each disease.
Amin Wu is a 24-year-old graduate who will join KAUST from the Communication University of China. Wu will join the University in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Environmental Statistics Research Group under the supervision of Professor Ying Sun. Wu wants to be a teacher or researcher and use her expertise and knowledge to make the world a better place.
Associate Professor Xin Gao and his group have developed an artificial-intelligence (AI) based solution to help increase COVID-19 testing accuracy. Identifying cases of early stage infection has been particularly challenging for frontline clinicians. Gao's AI-based model, which aims to increase accuracy, has been put to immediate use at King Faisal Specialist Hospital (KFSH) in Riyadh.
Extreme weather patterns and regions at risk of flooding could be easier to spot using a new statistical model for large spatial datasets.
Hashtags like #covid19 and #coronavirus help us stay up to date on the developments of the new coronavirus pandemic. But beyond breaking news, tweets also offer a glimpse into the emotional side of the COVID-19 crisis.
By training a search agent to make smarter exploratory decisions, relational data can be classified more accurately and efficiently.
Throughout the world, organic waste generation is posing serious challenges, threatening food security and water purity and availability. Saudi Arabia is no exception.
Gaurav Agarwal firmly believes in the age-old adage that patience is a virtue. Without patience, life’s challenges cannot be overcome, and a steadfast belief in perseverance has served the statistics Ph.D. student well throughout his academic career.
The future has already arrived when it comes to the most exciting and promising field of modern medicine—precision medicine.
Machine learning tasks using very large data sets can be sped up significantly by estimating the kernel function that best describes the data.
Wanfang Chen, a Ph.D. candidate in statistics, and member of Distinguished Professor Marc Genton’s Spatio-Temporal Statistics & Data Science (STSDS) research group, recently won a Student Paper Award sponsored by the Section on Statistics and the Environment (ENVR) of the American Statistical Association (ASA).
Pinpoint mesh of smart underground objects could give real-time 3D readout of fossil fuel reserves.