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).
Ghulam Qadir, a third-year Ph.D. student in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received a best poster award from the Italian Environmetrics Society (GRASPA) and the International Environmetrics Society (TIES) at the GRASPA 2019 conference held from July 15 to 16 in Pescara, Italy.
More accurate detection of hotspot clusters provides new insights into the behavior of air pollution.
The spatial variation in different air pollution components helps identify possible targets for pollution control.
Automatic detection of uncharacteristic data sequences could change the way data is processed and analyzed.
The latest statistical methods from research on complex high-dimensional environmental data also yield powerful tools for interpreting brain activity.
Carolina Euán, a postdoctoral fellow in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received the Sylvia Esterby Presentation Award from the International Environmentrics Society (TIES) at the 28th Annual TIES Conference 2018 held from July 16 to 21, 2018, in Guanajuato, Mexico. Euán won the award for her talk entitled "Bernoulli Vector Autoregressive Model with Applications to Spatio-temporal Drought Events in Mexico."