probability theory

Is probability theory the only viable solution to modelling statistical information?

Prof. Jeremie Houssineau, Department of Statistics, University of Warwick.

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KAUST

Many alternatives to the probabilistic modelling of information have been proposed since the birth of modern Statistics; yet, few have been successfully applied to the complex inference problems that modern Statisticians are faced with.

Kody J. H. Law

Senior Research Scientist, Stochastic Numerics Research Group
Kody J. H. Law worked as a Senior Research Scientist at Professor Raul F. Tempone's Stochastic Numerics Research Group (STOCHNUM) at King Abdullah University of Science and Technology (KAUST). Research Interests Kody specializes in computational approaches to inverse problems, uncertainty quantification, and sequential data assimilation. His interest spans methodology, such as function-space sampling and filtering algorithms, and also applications, such as numerical weather prediction, ocean prediction, climate prediction, and subsurface reconstruction. His interest in data assimilation

Kelvin J. R. Almeida-Sousa

Postdoctoral Research Fellow, Statistics
Kelvin J. R. Almeida-Sousa is a Brazilian mathematician with contributions to deterministic and stochastic partial differential equations, numerical analysis, mathematical statistics, and spectral theory.

Fabián Crocce

Postdoctoral Research Fellow, Stochastic Numerics Research Group
Fabián Crocce worked as a Postdoctoral Fellow​​ at Professor Raul F. Tempone's Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Partial Differential Equations, Probability Theory, and Stochastic Processes Distributed Strategic Learning, Stochastic Modeling. Optimal stopping for diffusions, both one-dimensional and multi-dimensional. Representation of the solution by the Green kernel of the process. His research interests also included optimal stopping problems for jump-processes and infinite-horizon problems. Fourier methods

Avetik Karagulyan

Postdoctoral Research Fellow, Optimization and Machine Learning
Avetik Karagulyan have joined the team of Peter Richtarik at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST) as a Postdoctoral fellow in November 2021. Education and Early Career Avetik Karagulyan has defended his thesis at Center of Research in Economics and Statistics (CREST), Paris in June 2021 entitled as "Sampling with the Langevin Monte-Carlo" under the supervision of professor Arnak Dalalyan. In 2018, he received MSc Mathematics, Vision, Learning (MVA) diploma at ENS Paris-Saclay with highest honors. Avetik Karagulyan graduated from

Alexandre de Bustamante Simas

Senior Research Scientist, Statistics
Alexandre Simas is an expert on stochastic processes and spatial statistics, with a focus on stochastic partial differential equations and random fields on metric graphs.

Adil Salim

Postdoctoral Research Fellow, Computer Science
Adil Salim is a Postdoctoral Research Fellow working with Professor Peter Richtarik at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Dr. Salim earned his Master degrees in Data Science and Statistical Engineering from ENSAE ParisTech and in Probability Theory and Stochastic Modeling from Paris XI University in France in 2015. He received his Ph.D. in Machine Learning from Télécom ParisTech in France in 2018. Before joining KAUST, Adil worked in many positions starting from an Auditor for banks and insurance companies