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David Bolin

Professor, Statistics

Principal Investigator, Stochastic Processes and Applied Statistics

Computer, Electrical and Mathematical Science and Engineering Division
Email icon david.bolin@kaust.edu.sa

In the Stochastic processes & applied statistics group, we develop statistical models and methods involving stochastic processes and fields for a wide range of applications.

Program Affiliations

Biography

David Bolin is a Professor of Statistics in the CEMSE Division at KAUST, where he leads the Stochastic Processes and Applied Statistics research group. Before joining KAUST, he was an associate professor of Mathematical Statistics at the University of Gothenburg. He received his Ph.D. in mathematical statistics from Lund University in 2012.

Bolin's research focuses on stochastic partial differential equations (SPDEs) and their applications in statistics, with an emphasis on developing practical, computationally efficient tools for modeling non-stationary and non-Gaussian processes. He has made significant contributions to the theory of Gaussian processes, optimal linear prediction, fractional-order SPDEs, and stochastic processes on metric graphs. He has also developed and maintains several widely used software packages for advanced statistical modeling.

Bolin serves as an associate editor for the Scandinavian Journal of Statistics, is an elected member of the International Statistical Institute, and has received multiple honors, including the Section on Statistics and the Environment Early Investigator Award from the American Statistical Association and the Cramér Prize from the Cramér section of the Swedish Statistical Society.

Research Interests

Professor Bolin’s main research interests are stochastic partial differential equations (PDEs) and their applications in statistics, focusing on developing practical, computationally efficient tools for modeling non-stationary and non-Gaussian processes.

The Swedish researcher leads the Stochastic Processes and Applied Statistics (StochProc) research group at KAUST, which focuses on statistical methodology for stochastic processes and random fields based on stochastic PDEs.

This research combines methods from statistics, probability and applied mathematics in order to construct more flexible statistical models and better computational methods for statistical inference. In parallel with the theoretical research, the group works on applications in a wide range of areas, ranging from brain imaging to environmental sciences.
Keyword tag icon
spatio-temporal statistics stochastic differential equations computational statistics

Education Profile

  • Postdoctoral Fellow, Umeå University, 2012-2013

  • Ph.D. Mathematical Statistics, Lund University, 2012

  • M.S. Engineering Mathematics, Lund University, 2007

Publications

  • D. Bolin, A. Simas and Z. Xiong (2024) Covariance-based rational approximations of fractional SPDEs for computationally efficient Bayesian inference, Journal of Computational and Graphical Statistics, 33(1), 64-74

  • D. Bolin, M. Kovács, V. Kumar, A. Simas (2024) Regularity and numerical approximation of fractional elliptic differential equations on compact metric graphs, Mathematics of Computation, 93, 2439-2472

  • D. Bolin, A. Simas and J. Wallin (2024) Gaussian Whittle-Matérn fields on metric graphs, Bernoulli, 30(2), 1611–1639

  • D. Bolin and J. Wallin (2023), Local Scale Invariance and Robustness of Proper Scoring Rules, Statistical Science, 38:1, 140-159

  • K. Kirchner and D. Bolin (2022) Necessary and sufficient conditions for asymptotically optimal linear prediction of random fields on compact metric spaces, Annals of Statistics, 50(2): 1038-1065

Research Areas

Multimedia