David Bolin

About David Bolin

David Bolin

Professor, Statistics

mathematical statistics random fields stochastic partial differential equations computational statistics stochastic processes

David Bolin is an expert on stochastic processes, random fields and spatial statistics. His main research focus is on stochastic partial differential equations and their applications in statistics.

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January 2026

Building bridges between mathematical statistics and real-world impact

4 min read · Tue, Jan 6 2026

Spotlight News Research in Focus

mathematical statistics random fields stochastic partial differential equations computational statistics

A research journey that connects statistical theory with the complexity of real-world systems.

October 2025

September 2025

Understanding Extremal Dependence in Lévy Driven Processes

1 min read · Sun, Sep 14 2025

News

Exponential tail Extremal dependence Moving average process Non-Gaussian process

A new study by researchers Zhongwei Zhang, David Bolin, Sebastian Engelke, and Raphaël Huser tackles the open problem of characterizing extreme event dependence in certain non-Gaussian stochastic processes. The work focuses on continuous-time moving average processes driven by exponential-tailed Lévy noise, models that extend classical Gaussian processes to capture heavy deviations and jump discontinuities. Until now, it was unclear how extremes in these models behave jointly across different spatial locations or time points, depending on the domain in which the process is defined. The

August 2025

Understanding Extreme Market Behavior: The Efficient Tail Hypothesis

2 min read · Thu, Aug 28 2025

News

extreme events market microstructure extreme statistics

A new study by researchers Junshu Jiang, James Richards, Raphaël Huser, and David Bolin introduces the Efficient Tail Hypothesis (ETH), an analogue of the Efficient Market Hypothesis focused on extreme events in financial markets. Drawing on extreme value theory, the team developed a novel statistical measure to evaluate whether asset markets remain informationally efficient even during rare, extreme fluctuations. Their findings not only challenge conventional wisdom on market efficiency but also open the door to identifying potential opportunities (and risks) that emerge during market

July 2025

June 2025

Efficient and Accurate Inference for Matérn Gaussian Processes on Intervals

1 min read · Mon, Jun 16 2025

News

Gaussian processes statistical inference

A new study by researchers at KAUST introduces a breakthrough method for statistical modeling with Matérn Gaussian processes, a popular tool in spatial statistics, machine learning, and the natural sciences. While Gaussian processes with stationary Matérn covariance functions (Matérn processes) are valued for their flexibility, their use with large datasets has been severely limited by the high computational cost of standard methods. The team has developed the first generally applicable approach that enables fast, linear-cost inference and prediction for Matérn processes on bounded intervals

May 2025

Mastering Network Spatial Statistics with the MetricGraph R Package

1 min read · Sat, May 24 2025

News

spatial statistics applied statistics Bayesian Statistics Log-Gaussian Cox process Gaussian processes latent Gaussian models

A new open-access mini-course is expanding access to advanced network spatial statistics through practical training with the MetricGraph package R, a powerful tool developed by David Bolin (KAUST), Alexandre B. Simas (KAUST), and Jonas Wallin (Lund University) for modeling data on network structures such as road systems and river basins. Presented by Bolin and Simas at the University of Glasgow during the “ INLA: Past, Present, and Future” workshop, the mini-course provides step-by-step tutorials, real datasets, and comprehensive R code, all freely available online, opening new avenues for

September 2023

Penalizing complexity for better stats

2 min read · Mon, Sep 11 2023

News

Applying a penalty for increasing complexity provides better control over flexible statistical models.

July 2023

MetricGraph: New R package for statistical analysis of data on networks

1 min read · Wed, Jul 5 2023

News

The newly developed MetricGraph package is now available on CRAN. The package facilitates creation and manipulation of metric graphs, such as street or river networks. Further facilitates operations and visualizations of data on metric graphs, and the creation of a large class of random fields and stochastic partial differential equations on such spaces. These random fields can be used for simulation, prediction and inference. In particular, linear mixed effects models including random field components can be fitted to data based on computationally efficient sparse matrix representations

March 2023

Congratulations to Yan for successfully defending her PhD thesis

1 min read · Tue, Mar 28 2023

Spotlight News

Multivariate extremes extreme weather

October 2022

Congratulations to Zhongwei for successfully defending his PhD thesis

1 min read · Tue, Oct 25 2022

Spotlight News

Multivariate extremes extreme weather

Left: Zhongwei before starting his PhD defense. Right: picture taken at the group dinner following the defense, with Zhongwei (center) and Prof. Raphael Huser (carrying a child next to Zhongwei)

May 2022

Professor Bolin earns American Statistical Association Section on Statistics and the Environment Early Investigator Award

2 min read · Thu, May 26 2022

News

award statistics environment

Prof. David Bolin has been selected for the American Statistical Association Section on Statistics and the Environment Early Investigator (ENVR) Award for his outstanding contributions to environmental statistics.

January 2022

New article in NeuroImage

1 min read · Sun, Jan 16 2022

News

statistics Functional Magnetic Resonance Imaging

The article Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups, which investigates the accuracy of SPDE-based models for cs-fMRI data, is now in press in NeuroImage.

August 2021

New article published in Journal of Climate

1 min read · Mon, Aug 30 2021

News

The paper Extreme rainfall events in the Northeastern USA become more frequent with rising temperatures, but their intensity distribution remains stable by Helga Olafsdottir, Holger Rootzén, and David Bolin has been published in Journal of Climate.

March 2021

Getting the inside track on street design

1 min read · Tue, Mar 30 2021

News

big data statistics

Large-scale analysis of pedestrian data from three European cities examines how building density and street design influence pedestrian behavior.

January 2021

New paper published in JRSS Series A

1 min read · Sun, Jan 10 2021

News

statistics machine learning

The paper Functional ANOVA modelling of pedestrian counts on streets in three European cities by David Bolin, Vilhelm Verendel, Meta Berghauser Pont, Ioanna Stavroulaki, Oscar Ivarsson, and Erik Håkansson has been published in the Journal of the Royal Statistical Society Series A.

December 2020

Prof. Bolin elected member of ISI

1 min read · Sat, Dec 26 2020

News

As of December 2020, David Bolin is an elected member of the International Statistical Institute. ISI Elected membership is open to individuals who are established in their careers and have made significant contributions to the statistical profession.

November 2020

Sci-Café on Statistics

1 min read · Mon, Nov 23 2020

News

statistics

Watch Sci-Café featuring panelists David Bolin, Hernando Ombao and Paula Moraga, with moderator Naadiya Carrim, by tuning in to the live Zoom feed, where you’ll be able to ask questions during the event, or by tuning in to the KAUST Official Facebook page or YouTube channel.

October 2020

Today we celebrate World Statistics Day!

1 min read · Tue, Oct 20 2020

News

statistics healthcare

Let’s discover the world of the statisticians at KAUST and be ready to be amazed by their cutting-edge research!

September 2020

Meet KAUST prospective student: Xiaotian Jin

1 min read · Thu, Sep 3 2020

News

Statistical Modeling spatio-temporal statistics

Xiaotian Jin is a graduate of Wenzhou-Kean University in China (a campus of Kean University in the USA). Xiaotian will join KAUST this fall as a M.S./Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics research group under the supervision of Professor David Bolin.

July 2020

KAUST Prospective Student: Damilya Saduakhas

2 min read · Sun, Jul 12 2020

News

machine learning Deep learning Natural Language Processing

Damilya Saduakhas, 21 years old, from Kazakhstan, obtained a B.Sc. degree in mathematics from the Nazarbayev University, Kazakhstan. Damilya has been selected as a young scientist to participate in the summer Data Lab from Yessenov Foundation and will join KAUST in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Stochastic Processes and Applied Statistics Research group under the supervision of Professor David Bolin.

April 2020

New Royal Statistical Society discussion paper

1 min read · Sat, Apr 4 2020

News

statistics

The manuscript Linear mixed effects models for non-Gaussian continuous repeated measurement data by Ozgur Asar, David Bolin, Peter J Diggle, and Jonas Wallin has been accepted as a Royal Statistical Society discussion paper. The paper will be presented at the discussion meeting on May 13, 2020. These meetings are usually held at the Society's premises in Errol Street, London. However, due to the current situation it will instead be a virtual meeting. See the related URLs for further details about the event and paper, and how to submit a contribution to the discussion.

December 2019

New paper published in JRSS Series B

1 min read · Tue, Dec 31 2019

News

The paper Multivariate type G Matérn stochastic partial differential equation random fields by David Bolin and Jonas Wallin has been published in the Journal of the Royal Statistical Society Series B.

November 2019

CEMSE New Faculty: David Bolin, Associate Professor of Mathematical Statistics

3 min read · Tue, Nov 19 2019

News

spatial statistics spatio-temporal modeling

David Bolin is an associate professor of mathematical statistics who joined the KAUST Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division earlier this month from the Department of Mathematical Sciences at the University of Gothenburg. Before joining KAUST, Bolin received both his Ph.D. degree in mathematical statistics and M.S.c in engineering mathematics from Lund University, Sweden, in 2012 and 2007, respectively. Upon completing his Ph.D., he spent one year at Umeå University, Sweden, working as a postdoctoral fellow before moving to the Chalmers University of Technology. In 2016, Bolin became an associate professor of mathematics at the University of Gothenburg, where a year later he received the title of Docent in mathematical statistics.