Research output per year
Research output per year
Personal profile
Research Overview
Professor Bolin's main research interests are in stochastic partial differential equations and their applications in statistics, with a focus on development of practical, computationally efficient tools for modelling non-stationary and non-Gaussian processes. He also works on uncertainty quantification and visualization for applications in spatial statistics and medical imaging.
Key Research Areas
Applied Mathematics and Computational Science, Machine Learning
Education
Mathematical Statistics, Ph.D., Lund University
2012
Engineering Mathematics, M.S., Lund University
2007
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Equivalence of measures and asymptotically optimal linear prediction for Gaussian random fields with fractional-order covariance operators
Bolin, D. & Kirchner, K., 2023, In: Accepted in Bernoulli.Research output: Contribution to journal › Article › peer-review
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Joint spatial modeling of significant wave height and wave period using the SPDE approach
Hildeman, A., Bolin, D. & Rychlik, I., Feb 9 2022, In: Probabilistic Engineering Mechanics. 68, p. 103203Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Local scale invariance and robustness of proper scoring rules
Bolin, D. & Wallin, J., Jan 1 2022, In: Statistical Science. -1, -1Research output: Contribution to journal › Article › peer-review
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NECESSARY AND SUFFICIENT CONDITIONS FOR ASYMPTOTICALLY OPTIMAL LINEAR PREDICTION OF RANDOM FIELDS ON COMPACT METRIC SPACES
Kirchner, K. & Bolin, D., Apr 7 2022, In: Annals of Statistics. 50, 2, p. 1038-1065 28 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups.
Spencer, D., Yue, Y. R., Bolin, D., Ryan, S. & Mejia, A. F., Jan 15 2022, In: NeuroImage. p. 118908Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
Template independent component analysis with spatial priors for accurate subject-level brain network estimation and inference
Mejia, A. F., Bolin, D., Yue, Y. R., Wang, J., Caffo, B. S. & Nebel, M. B., Jul 22 2022, In: Journal of Computational and Graphical Statistics. p. 1-35 35 p.Research output: Contribution to journal › Article › peer-review
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The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running
Lindgren, F., Bolin, D. & Rue, H., 2022, In: Accepted by Spatial Statistics.Research output: Contribution to journal › Article › peer-review
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Efficient methods for Gaussian Markov random fields under sparse linear constraints
Bolin, D. & Wallin, J., Jan 1 2021, 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Neural information processing systems foundation, p. 9882-9894 13 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution