Esmail Abdul Fattah
- Postdoctoral Research Fellow, Statistics
Biography
Esmail Abdul Fattah holds a Ph.D. in Statistics from KAUST, where he is now a postdoctoral researcher in high-performance computing. His work connects the two fields to scale Bayesian inference, bringing HPC to approximate methods such as INLA. This includes GPU-accelerated sparse factorizations and selected inversion for structured matrices through the sTiles framework, and extending INLA to non-sparse models. He also works on applications in spatial and spatio-temporal disease mapping.
More information: https://esmail-abdulfattah.github.io
Expertise and Interests
- Approximate Bayesian inference for latent Gaussian models
- Sparse and dense direct solvers, Cholesky factorization, and selected inversion
- GPU-accelerated and parallel numerical linear algebra, including tile algorithms
- Statistical software development
Awards and Distinctions
- Al-Kindi Research Award for outstanding Ph.D. research , Statistics Program, KAUST
- Best Presentation Award, 8th KAUST-NVIDIA Workshop on Accelerating Scientific Applications Using GPUs, KAUST
- Poster Award in Bayesian Computation, ISBA World Meeting 2022, Montreal, Canada, 2026
- KAUST Fellowship for doctoral studies, KAUST
- Full merit-based graduate fellowship and assistantship, AUB
- Full merit-based undergraduate scholarship, USAID, Haigazian University
- Outstanding Marketing Campaign Award and second place, Social Entrepreneurship Competition, Beyond Reform and Development, Beirut
Education
- Doctoral
- Statistics, KAUST, Saudi Arabia, 2023
- Master
- Computational Science, AUB, Lebanon, 2018
- Bachelor
- Computer Science and Mathematics, Haigazian University, Lebanon, 2015
Quote
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