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.
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."
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.
The KAUST Environmental Statistic (ES) research group has recently published a book titled "Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches." The book is the outcome of the Core Research Grant (GRG) project led by KAUST Professor Ying Sun, Associate Professor of Statistics.