A more accurate way of resolving spatial patterns in weather could lead to better predictions of climate change.
Harnessing the power of virtual reality will help to visualize data and improve statistical models.
A new statistical tool for collectively analyzing large sets of brainwaves promises to accelerate neurofunctional research.
KAUST second year Ph.D. student Yuxiao Li has been selected to receive a Student Paper Award from the American Statistical Association (ASA) for his paper entitled "Efficient Estimation of Non-stationary Spatial Covariance Functions with Application to High-resolution Climate Model Emulation."
KAUST second year Ph.D. student Yuxiao Li has been selected to receive a Student Paper Award from the American Statistical Association (ASA) for his paper entitled "Efficient Estimation of Non-stationary Spatial Covariance Functions with Application to High-resolution Climate Model Emulation."
KAUST Ph.D. alumna Sabrina Vettori and Ph.D. student Yuxiao Li have been selected by the Eastern North American Region (ENAR) of the International Biometric Society to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting.
KAUST Ph.D. student Yuxiao Li has been selected by the Eastern North American Region (ENAR) of the International Biometric Society to receive a Distinguished Student Paper Award at the 2018 ENAR Spring Meeting.
Married couple Wanfang Chen and Yuxiao Li came to KAUST in August 2016 to pursue their Ph.D. studies in the field of statistics. Both students are based in the University's Computer, Electrical and Mathematical Science & Engineering division—Chen under the supervision of Distinguished Professor Marc Genton and Li under the supervision of Professor Ying Sun.
Ying Sun is a multi-award-winning statistician who is inspired by the value of statistics in solving real-world problems.
Gaurav Agarwal joined KAUST in the fall of 2016 as a statistics Ph.D. student in the Environmental Statistics Group under the supervision of Professor Ying Sun. Before joining KAUST, Agarwal completed a bachelor's degree in statistics from Hindu College, Delhi, and a master's degree in statistics from the Indian Institute of Technology (IIT), Kanpur.
A method to visualize hidden statistical structure helps make sense of environmental data.
Ph.D. student Gaurav Agarwal received an Honorable Mention from ENVR student paper competition for his paper entitled "Quantile function modeling with application to salinity tolerance analysis in plant data."
Coordinated robot swarms can achieve amazing feats, but even a single faulty unit can have serious consequences.
2017 Workshop Modern Statistics for Complex Data Structures
A statistical technique for modeling large datasets improves interpretation of climate and environmental data.