collaborators

9 papers

cs.DC2026

Scaled Block Vecchia Approximation for High-Dimensional Gaussian Process Emulation on GPUs

Qilong Pan, Sameh Abdulah, Mustafa Abduljabbar +8

Emulating computationally intensive scientific simulations is crucial for enabling uncertainty quantification, optimization, and informed decision-making at scale. Gaussian Process…

stat.CO2026

MPCR: Multi-Precision Computations Package in R

Mary Lai O. Salvana, Sameh Abdulah, Minwoo Kim +3

In the early days of computing, severe memory constraints made it necessary to use lower floating-point precision. As hardware capabilities have advanced, modern systems, particula…

stat.CO2026

Fisher Scoring for Exact Matérn Covariance Estimation through Stable Smoothness Optimization

Yiping Hong, Sameh Abdulah, Marc G. Genton +1

Gaussian Random Fields (GRFs) with Matérn covariance functions have emerged as a powerful framework for modeling spatial processes due to their flexibility in capturing different…

cs.DC2025

High-Performance Statistical Computing (HPSC): Challenges, Opportunities, and Future Directions

Sameh Abdulah, Mary Lai O. Salvana, Ying Sun +2

We recognize the emergence of a statistical computing community focused on working with large computing platforms and producing software and applications that exemplify high-perfor…

stat.ME2025

Scalable Asynchronous Federated Modeling for Spatial Data

Jianwei Shi, Sameh Abdulah, Ying Sun +1

Spatial data are central to applications such as environmental monitoring and urban planning, but are often distributed across devices where privacy and communication constraints l…

cs.DC2025

RCOMPSs: A Scalable Runtime System for R Code Execution on Manycore Systems

Xiran Zhang, Javier Conejero, Sameh Abdulah +5

R has become a cornerstone of scientific and statistical computing due to its extensive package ecosystem, expressive syntax, and strong support for reproducible analysis. However,…