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!
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.
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 .
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.
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.
A universal high-performance computing interface allows popular statistical tools to run efficiently on large geospatial datasets.
Gaurav Agarwal, a fourth-year Ph.D. student in KAUST Associate Professor Ying Sun’s Environmental Statistics (ES) research group, recently won the best student paper award at the International Indian Statistical Association (IISA) 2019 Student Paper Competition for his paper titled “Bivariate Functional Quantile Envelopes with Application to Radiosonde Wind Data.”
Joining the faculty of King Abdullah University of Science and Technology (KAUST) six years ago gave statistics Professor Ying Sun a unique career opportunity: the chance to build and lead her own research group solving real-world problems.
From November 18 to 20 the KAUST CEMSE Division has hosted the 2019 Statistics and Data Science Workshop. The workshop, organized by Workshop Chair Professor Ying Sun from the KAUST Environmental Statistics Group, featured 17 keynote talks from eminent data science researchers from Asia, Europe, North America and on-campus.
Factors influencing the tolerance of barley to saline soils have been uncovered using an advanced robust statistical technique.
The 3 faculty positions are in the Statistics Program (http://stat.kaust.edu.sa) within the Computer, Electrical, and Mathematical Sciences and Engineering Division. Currently, the Statistics Program has 7 core faculty and 10 affiliated faculty. We are primarily interested in applicants with strong background in one of the following areas: (1) Statistical Data Science and AI, including network data analysis and high-dimensional statistics (https://apply.interfolio.com/69165); (2) Statistical Climatology, with expertise in statistical analysis of climate model output data, in particular regional climate models, and in physical systems (https://apply.interfolio.com/69167); (3) Statistics for Public Health, including smart health data analysis, personalized medicine, and disease mapping (https://apply.interfolio.com/69168).