David Bolin

Professor of statistics at @cemseKAUST

[KAUST CEMSE @KAUST_CEMSE]

From autonomous vehicles to environmental monitoring, #KAUST Statistics Professor David Bolin’s research focuses on developing statistical methods that make sense of complex, structured data.

Leading the Stochastic Processes and Mathematical Statistics group, Bolin and his team work at the interface of probability theory and real-world systems through stochastic partial differential equations (#PDEs). His research addresses challenges where traditional statistical assumptions break down, such as traffic data constrained by road networks and environmental data shaped by ocean dynamics.

These methods support applications ranging from traffic safety analysis, with the potential to inform evidence-based policy decisions, to early-warning models for ecological change in the Red Sea. By pairing methodological advances with accessible software, Bolin’s work emphasizes adoption, ensuring that theory translates into tools that can guide research, planning and policy.

Read more about how Bolin is bridging mathematical statistics and real-world impact: https://t.co/2zIY5p0EuA

#CEMSE #KAUSTStatistics #ReadSea #SmartCities #RedSeaResearch #StochasticPDEs #DataScience

[David Bolin @jdavidbolin]

Interesting workshop which also will have a tutorial on the MetricGraph package.

[R-INLA @bayescomp_inla]

INLA: past, present, and future. 21-23 May 2025 at the University of Glasgow. Registration at: https://t.co/boZjAmm1Ib

[David Bolin @jdavidbolin]

Great work about finding hotspots for traffic accidents using the MetricGraph and excursions packages.

[Damilya @thystat]

Thanks to the ISBA program Council for the acknowledgment! 🙂 #ISBA2024 @ISBA_events @j_ISBA

Thanks to my PI @jdavidbolin for all the support.

[R-INLA @bayescomp_inla]

Check out our latest paper on model checking for latent Gaussian models using  R-INLA and STAN by @Rafael_M_Cabral , @jdavidbolin , and @HavardRue1 :
https://t.co/6GvWWDZNVs

We propose a workflow to check model assumptions and the robustness of the statistical answers.
#RINLA

[David Bolin @jdavidbolin]

The paper on the approach that facilitates using SPDE models with arbitrary smoothness in @bayescomp_inla and @inlabru is now out in JCGS. The method recently won one of the 2023 KAUST competitions on Spatial Stats for Large Data, so it works really well.

https://t.co/5R9qahTRLU

[R-INLA @bayescomp_inla]

Huge congratulations 👏👏 to @Rafael_M_Cabral for successfully passing his PhD defense. He was advised by @jdavidbolin and @HavardRue1 and has made great contributions to latent non gaussian models.

[David Bolin @jdavidbolin]

After about one year of development, the MetricGraph #RStats package is now public! It facilitates working with data and random fields on linear networks and metric graphs, and has interfaces to @inlabru and @bayescomp_inla. For detailed tutorials, see

https://t.co/6ojRBfekpO

[David Bolin @jdavidbolin]

Last year, @Jonas_Wallin, @AlexandreBSimas and I wrote a paper on Gaussian fields on metric graphs. It was a bit dense, so it is now split it in three parts:

Regularity:
https://t.co/KdtS3cCBTk

Markov properties:
https://t.co/YfgrkP6YDU

Inference:
https://t.co/g2drbTn64S

[YoungStatS @YoungStatS2]

📝Read our new post by R. Cabral, D. Bolin & H. Rue (@KAUST_News) on fitting robust non-Gaussian models in Stan and R-INLA.
https://t.co/ZzY02cm63n

#statistics #blogpost
@StatFen @BernoulliSoc @InstMathStat

[David Bolin @jdavidbolin]

Great work by Rafael Cabral (student of Håvard Rue and me at @cemseKAUST) on fitting latent non-Gaussian models.

[David Bolin @jdavidbolin]

Version 1.2.0 of rSPDE is now on CRAN. One new feature is the support for using fractional SPDE models in @inlabru. See https://t.co/G7Fjq7EciO for details. #RINLA #rstats #rspatial

[David Bolin @jdavidbolin]

In December last year, @AlexandreBSimas and I updated the rSPDE package

https://t.co/oL5wqtT5QZ

with functions that facilitate using fractional SPDE models in R-INLA. The paper that describes the approach that was used to do this is now finally out:

https://t.co/HPtntiGPoI

[Instit. for Mathematical & Statistical Innovation @IMSI_Institute]

We're not slowing down with Expressing & Exploiting Structure in Modeling, Theory, & Computation w/ #Gaussian Processes, hearing talks by @jdavidbolin, @Princeton's Ruiyi Yang, @NorthwesternU's Matt Plumlee, @HoumanOwhadi, & @SandiaLabs's Mamikon Gulian
https://t.co/TNY20a6tAh

[David Bolin @jdavidbolin]

@ASeatonSpatial @millerdl @dan_p_simpson @FinnLindgren The problematic parameter is the range, not the smoothness. Even if the smoothness is fixed one cannot estimate the range consistently.

[David Bolin @jdavidbolin]

Looking forward to attending NORDSTAT again next year, where I will be organising a session about Gaussian processes on networks and graphs.

[NORDSTAT 2023 @nordstat2023]

first twitter announcement of NORDSTAT 2023, the 29th Nordic Conference in Mathematical Statistics! 19-22 June 2023 in Göteborg, Sweden.

Preliminary program at https://t.co/iS1qUCvowY

Register to the mailing list for more news. Retweets appreciated #nordstat2023

[Mandy Mejia, PhD @mandyfmejia]

Our paper on an ICA model for fMRI using surface-based spatial priors & empirical population priors was accepted at JCGS! Using spatial priors dramatically improves power to identify areas of the brain engaged in different functional networks. @jdavidbolin https://t.co/NLStR6iImW

[David Bolin @jdavidbolin]

Thanks, it was a nice surprise!

[KAUST CEMSE @KAUST_CEMSE]

Join us in congratulating David Bolin who earned the ASA Section on #Statistics and the #Environment Early Investigator (ENVR) Award for his outstanding contributions to environmental statistics. Well deserved, David! https://t.co/IyB9QEeCg5
@KAUST #cemseKAUST

[David Bolin @jdavidbolin]

@dan_p_simpson Thanks!! But some might argue that it is a great day when you need to prove your own Sobolev embedding theorem. :)

[David Bolin @jdavidbolin]

New paper about Gaussian processes on metric graphs, such as street networks. With @Jonas_Wallin and Alexandre Simas. This took a long time to develop, but I am really happy about the outcome. R implementations for INLA etc are coming soon.

https://t.co/KdtS3cCBTk