Uppsala universitet 
Stefan Engblom
Short CV: (pdf)
Publications: (pdf)

Stefan Engblom

Stefan Engblom
Associate professor, 
Docent in Scientific Computing and Numerical Analysis
Office Phone
+46 18 471 27 54 
+46 18 51 19 25 
Mailing Address
Scientific Computing
Information Technology
Box 337
SE-751 05 Uppsala
Visiting Address
Polacksbacken Building 2
Room 2414a
         Find me at the Mathematics Genealogy Project...
...at the Research Gate...
...at Google Scholar...
...at ORCID....
...at ResearcherID....
...at GitHub.

I am...
...the Head of the Division of Systems and Control...
...the program coordinator for the Master's programme in Computational Science...
...the current faculty advisor of UPPSALA SIAM Chapter...

On the national side I am an elected member of the Young Academy of Sweden for the period 2016--2021. See my presentation web-page there.

Swedish Young Academy

Latest news and upcoming activities


  • October 30: I will give a lecture in the Applied Mathematics Seminars-series at the University of Warwick.
  • November 25--26: Academy meeting, Örebro.
  • December 7: acting as PhD opponent, Lund.
  • December 18: acting as a member of a PhD committee, Gothenburg.


I am interested in most aspects of Scientific Computing, in Numerical Modeling and -Analys in particular, as well as to some extent in High-Performance Computing. My main focus of applications are in the Biosciences at broad, but I've also taken an interest in Engineering applications, and in Data-driven research. Current active research projects include multiscale modeling and parameterization of living cells in a population and Bayesian approaches for compute intensive spatial stochastic data-driven models in epidemics.

In case you are interested in doing a project work or a MSc-thesis, please feel invited to contact me for further discussions.

Read more (including publications and talks).

Open project proposals:
Computational cell population models: multiscale and multiphysics modeling

There are several openings for interesting and challenging projects within the software framework URDME. Suggestions include high-performance software development, advanced new modeling, and improving simulation efficiency and flexibility, as well as machine learning and data mining techniques. Precise suggestions for projects suitable to MSc/BSc-theses can be formulated upon request.
More details can be found here.


Spring 2020: Scientific Computing I 1TD393 (5.0hp).
Spring 2020: Numerical methods in stochastic modeling and simulations (7.5hp, graduate course).
Fall 2019: Scientific Computing II 1TD395 (5.0hp).
Previously also given 2018, 2017, 2016, 2015.
Spring 2019: Numerical Functional Analysis (7.5hp, graduate course)
Fall 2017:Advanced Numerical Methods 1TD050 (10.hp)
Fall 2016: Advanced Numerical Methods 1TD050 (10.hp)
Spring 2016: Numerical methods in stochastic modeling and simulations (7.5hp, graduate course).
Fall 2014: Numerical Functional Analysis (5.0hp, graduate course).
Spring 2014: Finite element methods II 1TD254 (5.0hp).
Fall 2012: Finite element methods 1TD253 (5.0hp).
Spring 2012: Classic Articles in Numerical Analysis (7.5hp, graduate course).
Fall 2010: Finite element methods 1TD253 (5.0hp).

Stefan Teaching Stefan Teaching


Please feel free to and use my software (Matlab/C/Mex) under a very liberal license. The software provided here includes a fairly wide range of subroutines useful in research, computations and for fun.

Please mail comments, suggestions, references, criticism. Please do not send support questions.

Download here.


If a picture tells more than a thousand words then a GIF-animation should tell at least a million...

SimInf and Data-driven epidemiological simulations:

URDME simulating stochastic spatial kinetics:
Surfactant in two-phase fluid flow (simulations by Minh Do-Quang):
Fibers in Stokes flow:
The master equation:
Autotuning (simulation by Marcus Holm):
Flow around airfoils (simulations by Paul Deglaire):


I am involved in teaching Tango at Tangogruppen Cambalache.


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