Profiles

Mary Lai Salvana is an assistant professor of statistics at the University of Connecticut. She earned her Ph.D. in statistics from King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Before joining the University of Connecticut, she held a postdoctoral fellowship in the Department of Mathematics at the University of Houston. She received her bachelor’s and master’s degrees in applied mathematics from Ateneo de Manila University in the Philippines in 2015 and 2016, respectively.

Her research focuses on the statistical modeling of extreme and catastrophic events, risk and disasters, with an emphasis on spatial and spatio-temporal statistics, environmental and computational statistics, large-scale data science, and high-performance computing.

• Multivariate space-time statistics
• Environmental statistics
• High performance computing
• Extreme events, risks, disasters
• Climate change

Małgorzata Forystek is a Statistics Master's student at the Bayesian Computational Statistics & Modeling research group  (BAYESCOMP) under the supervision of Professor Håvard Rue. She received her B.Sc. degree in Applied Mathematics from AGH University of Science and Technology in Kraków, Poland, in 2023.

Her research interest is mainly in Bayesian and computational Statistics and Data Science.

Sihan Chen joined the PhD program in Statistics at King Abdullah University of Science and Technology (KAUST) in 2021, under the supervision of Prof. Marc G. Genton. Prior to that, he received his Bachelor’s and Master’s degrees from The Chinese University of Hong Kong. Sihan's doctoral research focused on developing robust and scalable statistical methods for spatial data analysis. His research interests include spatial statistics, robust estimation, high-performance computing, and applied data science.

Zipei Geng completed his undergraduate education in 2019 with a Bachelor of Science in Statistics from Shandong University, alongside a dual Bachelor of Science with Honours in Statistics from The University of Manchester. He subsequently pursued a Master of Science in Statistics at ETH Zurich (Eidgenoessische Technische Hochschule Zuerich) from 2019 to 2022, where his studies concentrated on variable selection and high-dimensional statistics. Currently, he is pursuing his doctoral studies as a PhD candidate in Statistics at King Abdullah University of Science and Technology, working under the guidance of Prof. Marc G. Genton.

Janet van Niekerk is a Research Scientist in the Bayesian Computational Statistics and Modeling group. She works on Bayesian methods including prior construction and computational framework development for various applications, with a focus on Biostatistics.

Efficient Bayesian methods for practical implementation, statistics for medical applications, complex survival analysis, INLA.