Publications

• Available via arXiv.

E. Blom, S. Engblom: Morphological stability for in silico models of avascular tumors

• In Bull. Math. Biol, 86 (2024) (doi).
• Available via arXiv.

E. Blom, S. Engblom, G. Menz: Modeling the hallmarks of avascular tumors

• Available via arXiv.

R. Marin, H. Runvik, A. Medvedev, and S. Engblom: Bayesian Monitoring of COVID-19 in Sweden

• In Epidemics, 45 (2023) (doi).
• Available via arXiv.
• Reproduce the numerical experiments: download from GitHub.
• DiVA record.

S. Bronstein, S. Engblom, and R. Marin: Bayesian inference in Epidemics: linear noise analysis

• In Math. Biosci. Eng., 20(2) (2023):4128–4152 (doi).
• Available via arXiv.
• Reproduce the numerical experiments: BISDE.tar (requires Matlab, R, and relies on URDME and SimInf).
• DiVA record.

B. Kennedy, H. Fitipaldi, U. Hammar, et al.: App-based COVID- 19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden

• In Nature Commun., 13(2110) (2022) (doi).
• DiVA record.

F. Wrede, R. Eriksson, R. Jiang, L. Petzold, S. Engblom, A. Hellander, and P. Singh: Robust and integrative Bayesian neural networks for likelihood-free parameter inference

• At the 2022 International Joint Conference on Neural Networks (IJCNN) at IEEE WCCI 2022 (doi).
• Preprint at arXiv.
• DiVA record.

J. Bull and S. Engblom: Distributed and Adaptive Fast Multipole Method In Three Dimensions

• In Commun. Comput. Phys. 30(4):959–984 (2021): (doi)
• Available via arXiv.
• DiVA record.
• Download the daFMM3D software at www.stenglib.org.

S. Engblom, R. Eriksson, P. Vilanova: Towards Confident Bayesian Parameter Estimation in Stochastic Chemical Kinetics

• In Numerical Mathematics and Advanced Applications: ENUMATH 2019, Lecture Notes in Computational Science and Engineering 139, 373–380 (2021): (doi).
• DiVA record.

J. Liu, S. Engblom, C. Nettelblad: Flash X-ray diffraction imaging in 3D: a proposed analysis pipeline

• In J. Opt. Soc. Amer. A 37(10):1673–1686 (2020) (doi).
• DiVA record.
• Available via arXiv.

S. Engblom, R. Eriksson, and S. Widgren: Bayesian epidemiological modeling over high-resolution network data

• In Epidemics 32 (2020) (doi).
• Available via arXiv.
• DiVA record.

H. Runvik, A. Medvedev, R. Eriksson, and S. Engblom: Initialization of a disease transmission model

• In Proceedings of the 3rd IFAC Workshop on Cyber-Physical & Human Systems, IFAC-PapersOnLine 53(5):839–844 (2020) (doi).
• Available via arXiv.
• DiVA record.

S. Engblom et al.: The URDME Manual version 1.4

• Available via arXiv.
• Download URDME 1.4 at www.urdme.org.

S. Widgren, P. Bauer, R. Eriksson, and S. Engblom: SimInf: An R package for data-driven stochastic disease spread simulations

• In J. Stat. Softw., 91(12):1–42 (2019) (doi).
• DiVA record.
• Available via arXiv.
• Download the latest version of SimInf at www.siminf.org.

J. Lindén, P. Bauer, S. Engblom, and B. Jonsson: Exposing inter-process information for efficient PDES of spatial stochastic systems on multicores

• In ACM Trans. Model. Comput. Simul., 29(2):11:1–25 (2019) (doi).
• DiVA record.

J. Liu, G. Schot, S. Engblom: Supervised Classification Methods for Flash X-ray single particle diffraction Imaging

• In Opt. Express, 27(4):3884–3899 (2019) (doi).
• DiVA record.
• Available via arXiv.

S. Engblom: Stochastic simulation of pattern formation in growing tissue: a multilevel approach

• In Bull. Math. Biol., 81:3010–3023 (2019) (doi).
• DiVA record.
• Available via arXiv.

D. Arjmand, S. Engblom, G. Kreiss: Temporal upscaling in micro magnetism via heterogeneous multiscale methods

• In J. Comput. Appl. Math. 345:99–113 (2019) (doi).
• DiVA record.
• Available via arXiv.

S. Widgren, T. Rosendal, S. Engblom, and K. Ståhl: SimInf for spatio-temporal data-driven modeling of African swine fever in Swedish wildboar

• In GeoVet 2019: Novel spatio-temporal approaches in the era of Big Data (url)

S. Engblom, P. Lötstedt, L. Meinecke: Mesoscopic Modeling of Random Walk and Reactions in Crowded Media

• In Phys. Rev. E 98(3):033304 (2018): (doi).
• DiVA record. Note: illustration seclected for the Phys. Rev. E Kaleidoscope in September 2018!
• Available via arXiv.

S. Widgren, S. Engblom, U. Emanuelson, and A. Lindberg: Spatio-temporal modelling of verotoxigenic _Escherichia coli O157 in cattle in Sweden: Exploring options for control_

• In Veterinary Res. 49(78), (2018): (doi).
• DiVA record.

S. Engblom, D. Wilson, R. Baker: Scalable population-level modeling of biological cells incorporating mechanics and kinetics in continuous time

• In Roy. Soc. Open Sci. 5(8), (2018): (doi).
• DiVA record.
• Available via arXiv.

P. Bauer, S. Engblom, S. Mikulovic, and A. Senek: Multiscale modeling via split-step methods in neural firing

• In Math. Comput. Model. Dyn. Syst. 24(4):409–425, (2018): (doi).
• DiVA record.
• Available via arXiv.

J. Liu, S. Engblom, and C. Nettelblad: Assessing Uncertainties in X-ray Single-particle Three-dimensional reconstructions

• In Phys. Rev. E. 98(1):013303, (2018): (doi).
• DiVA record. Note: illustration seclected for the Phys. Rev. E Kaleidoscope in July 2018!
• Preprint via arXiv.

A. Goude, S. Engblom: A general high order two-dimensional panel method

• In Appl. Math. Model. 60:1–17 (2018): (doi).
• DiVA record.
• Available via arXiv.

A. Chevallier and S. Engblom: Pathwise error bounds in multiscale variable splitting methods for spatial stochastic kinetics

• In SIAM J. Numer. Anal. 56(1):469–498, (2018) (doi).
• DiVA record.
• Available via arXiv.

J. Lindén, P. Bauer, S. Engblom, B. Jonsson: Fine-Grained Local Dynamic Load Balancing in PDES

• In Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM PADS ‘18, pages 201–2012 (2018): (doi).
• DiVA record.

R. Eriksson, S. Engblom, and S. Widgren: Towards Bayesian parametrization of national scale epidemics

• In MATHMOD 2018 Extended Abstract Volume, ARGESIM(55), p. 65–66 (2018): (doi) * DiVA record.

S. Engblom and S. Widgren: Data-driven computational disease spread modeling: from measurement to parametrisation and control

• Chapter 11 in Disease Modelling and Public Health, Part A, Volume 36 of Handbook of Statistics, (doi).
• DiVA record.

S. Engblom: Stability and Strong Convergence for Spatial Stochastic Kinetics

• Chapter 3.3 in Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology, (doi).
• DiVA record.

S. Engblom, A. Hellander, P. Lötstedt: Multiscale Simulation of Stochastic Reaction-Diffusion Networks

• Chapter 2.4 in Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology, (doi).
• DiVA record.

G. Christoffersson, J. Lomei, P. O’Callaghan, J. Kreuger, S. Engblom, and M. Phillipson: Vascular sprouts induce local attraction of proangiogenic neutrophils

• In J. Leukocyte Biol. 102(3):741–751, (2017): (doi).
• DiVA record.

J. Lindén, P. Bauer, S. Engblom, B. Jonsson: Exposing inter-process information for efficient parallel discrete event simulation of spatial stochastic system

• In Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM PADS ‘17, pages 53–64, (2017): (doi).
• DiVA record.

A. Senek and S. Engblom: Multiscale Stochastic Neuron Modeling - with Applications in Deep Brain Stimulation (Wip)

• In Proceedings of the Summer Simulation Multi-Conference, Summer-Sim ‘17, pages p. 38:1–38:5 (2017): (ACM URL) * DiVA record.

P. Bauer, S. Engblom: The URDME Manual version 1.3

• Technical report: (abstract), (pdf)
• Available via arXiv.
• Download URDME 1.3 at www.urdme.org.

S. Widgren, S. Engblom, P. Bauer, J. Frössling, U. Emanuelson, and A. Lindberg: Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle

• In Veterinary Res. 47:81(1):1–17, (2016). (doi).
• DiVA record.

S. Engblom, D. Lukarski: Fast Matlab compatible sparse assembly on multicore computers

• In Parallel Comput. 56:1–17 (2016) (doi).
• Preprint via arXiv.
• DiVA record.

E. Blanc, S. Engblom, A. Hellander, P. Lötstedt: Mesoscopic modeling of stochastic reaction-diffusion kinetics in the subdiffusive regime

• In Multiscale Model. Simul. 14(2):668–707 (2016): (doi).
• Preprint via arXiv.
• DiVA record.

P. Bauer, S. Engblom, S. Widgren: Fast event-based epidemiological simulations on national scales

• In Int. J. High Perf. Comput. Appl. 30(4):438–453 (2016): (doi).
• Preprint via arXiv.
• DiVA record.

L. Meinecke, S. Engblom, A. Hellander, and P. Lötstedt: Analysis and design of jump coefficients in discrete stochastic diffusion models

• In SIAM J. Sci. Comput. 38(1):A55–A83 (2016): (doi).
• Preprint via arXiv.
• DiVA record.

S. Engblom and V. Sunkara: Preconditioned Metropolis sampling as a strategy to improve efficiency in posterior exploration

• In IFAC-PapersOnLine 49(26):89–94 (2016): (doi).
• DiVA record.

J. Bull, S. Engblom, and S. Holmgren: A direct solver for the advection-diffusion equation using Green’s functions and low-rank approximation

• In proceedings of the 7th ECCOMAS Congress, European Community on Computional Methods in Applied Sciences (ECCOMAS 2016): (direct link).
• DiVA record.

A. Milias-Argeitis, S. Engblom, P. Bauer, M. Khammash: Stochastic focusing coupled with negative feedback enables robust regulation in biochemical reaction networks

• In J. R. Soc. Interface 12(113):1–10 (2015): (doi).
• Preprint via arXiv.
• DiVA record.

S. Engblom: Strong convergence for split-step methods in stochastic jump kinetics

• In SIAM J. Numer. Anal. 53(6):2655–2676 (2015): (doi)
• DiVA record.
• Review: MR3432851.
• Preprint via arXiv.

T. Ekeberg, S. Engblom, J. Liu: Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

• In Int. J. High Perf. Comput. Appl. 29(2):233–243 (2015): (doi)
• Available via arXiv.
• DiVA record.

P. Bauer, J. Lindén, S. Engblom, B. Jonsson: Efficient interprocess synchronization for parallel discrete event simulation on multicores

• In Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM PADS ‘15, pages 183–194, (2015): (doi).
• DiVA record.

P. Bauer, S. Engblom: Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics

• In Numerical Mathematics and Advanced Applications: ENUMATH 2013, Lecture Notes in Computational Science and Engineering 103, 519–527 (2015): (doi).
• DiVA record.

S. Engblom: On the stability of stochastic jump kinetics

• In Appl. Math. 5(19):3217–3239 (2014) (doi).
• DiVA record.
• Preprint via arXiv.
• Technical report: (abstract), (pdf).

M. Holm, S. Engblom, A. Goude, S. Holmgren: Dynamic autotuning of adaptive fast multipole methods on hybrid multicore CPU & GPU systems

• In SIAM J. Sci. Comput. 36(4):C376–C399 (2014): (doi)
• DiVA record.
• Review: MR3253697.
• Preprint via arXiv.

S. Engblom, J. Liu: X-ray laser imaging of biomolecules using multiple GPUs

• In Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science:480–489, 2014: (doi).
• DiVA record.

S. Engblom, J. Pender: Approximations for the moments of nonstationary and state dependent birth-death queues

• Available via arXiv.
• DiVA record.

A. Goude and S. Engblom: Adaptive fast multipole methods on the GPU

• In J. Supercomput 63(3):897–918, 2013: (doi)
• DiVA record.
• Preprint at arXiv.
• Technical report: (abstract), (pdf).

S. Engblom, M. Do-Quang, G. Amberg, A-K. Tornberg: On diffuse interface modeling and simulation of surfactants in two-phase fluid flow

• In Commun. Comput. Phys. 14(4):879–915, 2013: (doi).
• DiVA record.
• Preprint at arXiv.

K. Mattsson, M. Almquist, S. Engblom: Stable and accurate wave simulations in complex geometries and discontinuous media

• In proceedings of the 11th International Conference on Mathematical and Numerical Aspects of Waves (WAVES 2013), (direct link).
• DiVA record.

M. Do-Quang, S. Engblom, A-K. Tornberg, G. Amberg: The well-posedness of diffuse interface modeling of surfactants in two-phase fluid flow

• In proceedings of the 1st International workshop on Wetting and evaporation: droplets of pure and complex fluids
• DiVA record.

B. Drawert, S. Engblom, and A. Hellander: URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries

• In BMC Syst. Biol. 6(76):1–17, 2012: (doi).
• DiVA record.

P. Bauer, B. Drawert, S. Engblom, A. Hellander: URDME v. 1.2: User’s manual

• Technical report: (abstract), (pdf)
• Also available via arXiv.
• Download URDME 1.2 from www.urdme.org.

P. Bauer, S. Mikulovic, S. Engblom, K. E. Leao, F. Rattay, and R. N. Leao: Finite element analysis of neuronal electric fields: the effect of heterogeneous resistivity

• Preprint at arXiv.

S. Engblom: On well-separated sets and fast multipole methods

• In Appl. Numer. Math. 61(10):1096–1102, 2011: (doi)
• DiVA record.
• Review: MR2820968
• Preprint at arXiv.

B. Drawert, S. Engblom, A. Hellander: URDME v. 1.1: User’s manual

• Technical report: (abstract), (pdf)
• Also available via arXiv.
• Download URDME 1.1 from www.urdme.org.

(2009) S. Engblom: Parallel in Time Simulation of Multiscale Stochastic Chemical Kinetics

• In Multiscale Model. Simul. 8(1):46–68, 2009: (doi)
  Reached #2 and #3 at the top 20 list of most downloaded papers in Multiscale Model. Simul. for the months October and September 2009, respectively.
• DiVA record.
• Review: MR2575044
• Technical report: (abstract), (pdf)
• Preprint at arXiv.

(2009) S. Engblom, L. Ferm, A. Hellander, P. Lötstedt: Simulation of Stochastic Reaction-Diffusion Processes on Unstructured Meshes

• In SIAM J. Sci. Comput. 31(3):1774–1797, 2009: (doi). Note: as of May/June 2018 this item is a Web of Science Highly cited paper.
• DiVA record.
• Review: MR2491545 (2010e:60142)
• Technical report: (abstract), (pdf)
• Preprint at arXiv.

(2009) S. Engblom: Spectral Approximation of Solutions to the Chemical Master Equation

• In J. Comput. Appl. Math. 229(1):208–221, 2009: (doi)
• DiVA record.
• Review: MR2522514 (Unfortunately, this review is not accurate)

(2009) S. Engblom: Galerkin Spectral Method applied to the Chemical Master Equation

• In Commun. Comput. Phys. 5(5):871–896, 2009: (abstract), (pdf)
• DiVA record.

(2009) P. Deglaire, S. Engblom, O. Ågren, H. Bernhoff: Analytical solutions for a single blade in vertical axis turbine motion in two-dimensions

• In Eur. J. Mech. B Fluids 28(4):506–520, 2009: (doi)
  The #1 most downloaded paper in Eur. J. Mech. B Fluids during the period April 2009–March 2011!
• DiVA record.

(2008) S. Engblom, PhD-thesis: Numerical Solution Methods in Stochastic Chemical Kinetics

• DiVA record
• Fulltext (pdf)

(2008) S. Engblom: Time-parallel simulation of stochastic chemical kinetics

• In proceedings of the International Conference on Numerical Analysis and Applied Mathematics (ICNAAM 2008) (doi)
• DiVA record.

(2008) S. Engblom, J. Cullhed, A. Hellander: The URDME Manual version 1.0

• Technical report: (abstract), (pdf)
• Also available via arXiv.
• Download URDME 1.0 through the download-link.

(2006) S. Engblom, Licentiate-thesis: Numerical methods for the chemical master equation

• DiVA record.

(2006) S. Engblom: Computing the Moments of High Dimensional Solutions of the Master Equation

• In Appl. Math. Comput. 180(2):498–515, 2006: (doi)
• DiVA record.
• Technical report: (abstract), (pdf)

(2006) S. Engblom: Gaussian quadratures with respect to discrete measures

• Technical report: (abstract), (pdf)
• DiVA record.