A new exascale climate emulator marks a significant advancement as the first to generate, display, and evaluate hourly emulations. This achievement has led an interdisciplinary research team from KAUST to be named a finalist for the prestigious Gordon Bell Prize in Climate Modelling.
A "deep" many-layered neural network does the heavy lifting in calculating accurate predictions from large complex environmental datasets.
Machine learning techniques can provide accurate forecasting of the spread of viruses during pandemics. Under the supervision of Ying Sun and Fouzi Harrou, Yasminah Alali developed an approach that removes human bias and assumptions, predicting pandemic evolution more accurately.
Faisal Fadi Hasan Almulla, who worked last year under the mentorship of Dr. Fouzi Harrou and Professor Ying Sun as part of the annual KAUST Saudi Research Science Institute (SRSI) summer program, won two awards at the National Olympiad for Scientific Creativity — Ibdaa 2022.
To address the growing threat of cyberattacks on industrial control systems, a KAUST team including Fouzi Harrou, Wu Wang and led by Ying Sun has developed an improved method for detecting malicious intrusions.
Qilong Pan is a statistics graduate who joined KAUST in June 2021 from the Wuhan University of Technology, China. Pan is a M.S./Ph.D. student and member of the Environmental Statistics research group under the supervision of Professor Ying Sun.
Statistical tools help fine-tune the parameters and approximations of models used to make sense of large spatial datasets.
Dr. Fouzi Harrou, a research scientist in the KAUST Environmental Statistics (ES) group, recently received two IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability 2021 (IEEE ECBIOS 2021) best paper awards.
A mixed-precision approach for modeling large geospatial datasets can achieve benchmark accuracy with a fraction of the computational run time.
Introducing KAUST’s very own "THE FANTASTATISTICS 4." Gaurav Agarwal, Jian Cao, Wanfang Chen, and Yuxiao Li are four Ph.D. alumni from the Statistics program at KAUST. The four students obtained their Ph.D.s last year under the supervision of Professor Ying Sun, Agarwal and Li, and Distinguished Professor Marc Genton, Cao and Chen, respectively.
Gaurav Agarwal, a Ph.D. candidate in statistics and member of KAUST Associate Professor Ying Sun's Environmental Statistics (ES) research group, recently won an American Statistical Association (ASA) Student Paper Award sponsored by the Sections on Computing and Graphics (SCSG). In addition to his ASA SCSG award, Agarwal has also been selected a Distinguished Student Paper Award winner by the Eastern North American Region (ENAR) of the International Biometric Society for his paper titled "Flexible Quantile Contour Estimation for Multivariate Functional Data: Beyond Convexity."
A high-frequency model developed using data from new high-precision rain gauges gives fresh insight into the dynamics of rain and runoff events.
Members of the KAUST American Statistical Association (ASA) student chapter recently came together for the group’s second online meeting held on Tuesday, November 10, 2020. The meeting served as an orientation exercise for new KAUST Statistics (STAT) Program students while also highlighting the shared experience of STAT Ph.D. candidates: Jian Cao, Wanfang Chen, Yuxiao Li, and Gaurav Agarwal.
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments.
Let’s discover the world of the statisticians at KAUST and be ready to be amazed by their cutting-edge research!