Statistical Modeling

Gaussian Random Fields on Metric Graphs

David Bolin, Professor, Statistics

Sep 11, 12:00 - 13:00

B9 B2 L2325

Gaussian random fields Metric graphs Statistical Modeling

This talk presents a comprehensive mathematical and statistical theory, along with user-friendly software, for modeling data with Gaussian random fields on metric graphs by developing valid covariance functions based on network distance.

Andrea Vanessa Rocha

Research Specialist, Statistics

Statistical Modeling computational statistics machine learning stochastic processes

Meet KAUST prospective student: Xiaotian Jin

1 min read · Thu, Sep 3 2020

Statistical Modeling spatio-temporal statistics

Xiaotian Jin is a graduate of Wenzhou-Kean University in China (a campus of Kean University in the USA). Xiaotian will join KAUST this fall as a M.S./Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics research group under the supervision of Professor David Bolin.

Xiaotian Jin

Ph.D. Student, Statistics

Statistical Modeling spatio-temporal statistics

Xiaotian Jin is a Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics research group under the supervision of Professor David Bolin. Before joining KAUST, Xiaotian obtained a bachelor's degree in computer science from Wenzhou-Kean University, China. Research Interests Xiaotian's research interests include statistical modeling and Spatio-temporal statistics.