Turning your desktop to a Supercomputer with ExaGeoStatR
Download at https://github.com/ecrc/exageostatR.
Remember the old times where you had to leave your R simulations running for the whole night on your desktop due to a large climate/weather dataset?
Xiaotian Jin is a graduate of Wenzhou-Kean University in China (a campus of Kean University in the USA). Xiaotian will join KAUST this fall as a M.S./Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics research group under the supervision of Professor David Bolin.
Machine learning models can rapidly and accurately estimate key chemical parameters related to molecular reactivity.
Cristian Felipe Jiménez Varón is an applied mathematics graduate who will join KAUST from the Universidad Nacional de Colombia Sede Manizales (UNAL), Colombia. He also holds dual bachelor's degrees in industrial engineering and chemical engineering fromUNAL .
Following a call by President Tony Chan for KAUST PIs to contribute through their research capabilities to alleviate the COVID-19 pandemic, efforts coordinated by Donal Bradley, KAUST vice president for research, and Pierre Magistretti, KAUST dean of the Biological and Environmental Science and Engineering division, mobilized a group of faculty to form the Rapid Research Response Team (R3T).
High-resolution analysis of wind speed across Saudi Arabia can help fast track the expansion of the Kingdom’s emerging world-class wind energy industry.
The global, multifarious challenge posed by the COVID-19 pandemic has scientists tapping their wide-ranging fields of expertise to attack the problem on many fronts. Answering the call from KAUST President Tony Chan, and coordinated by the University's leadership team, KAUST researchers making up the Rapid Research Response Team (R3T) are turning this crisis into an opportunity to innovate.
Damilya Saduakhas, 21 years old, from Kazakhstan, obtained a B.Sc. degree in mathematics from the Nazarbayev University, Kazakhstan. Damilya has been selected as a young scientist to participate in the summer Data Lab from Yessenov Foundation and will join KAUST in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics Research group under the supervision of Professor David Bolin.
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.